The various differential expression analyses of the data generated in tmrc3_datasets will occur in this document.
I am going to try to standardize how I name the various data structures created in this document. Most of the large data created are either sets of differential expression analyses, their combined results, or the set of results deemed ‘significant’.
Hopefully by now they all follow these guidelines:
{clinic(s)}sample-subset}{primary-question(s)}{datatype}{batch-method}
With this in mind, ‘tc_biopsies_clinic_de_sva’ should be the Tumaco+Cali biopsy data after performing the differential expression analyses comparing the clinics using sva.
I suspect there remain some exceptions and/or errors.
Each of the following lists describes the set of contrasts that I think are interesting for the various ways one might consider the TMRC3 dataset. The variables are named according to the assumed data with which they will be used, thus tc_cf_contrasts is expected to be used for the Tumaco+Cali data and provide a series of cure/fail comparisons which (to the extent possible) across both locations. In every case, the name of the list element will be used as the contrast name, and will thus be seen as the sheet name in the output xlsx file(s); the two pieces of the character vector value are the numerator and denominator of the associated contrast.
<- list(
clinic_contrasts "clinics" = c("Cali", "Tumaco"))
## In some cases we have no Cali failure samples, so there remain only 2
## contrasts that are likely of interest
<- list(
tc_cf_contrasts "tumaco" = c("Tumacofailure", "Tumacocure"),
"cure" = c("Tumacocure", "Calicure"))
## In other cases, we have cure/fail for both places.
<- list(
clinic_cf_contrasts "cali" = c("Califailure", "Calicure"),
"tumaco" = c("Tumacofailure", "Tumacocure"),
"cure" = c("Tumacocure", "Calicure"),
"fail" = c("Tumacofailure", "Califailure"))
<- list(
cf_contrast "outcome" = c("Tumacofailure", "Tumacocure"))
<- list(
t_cf_contrast "outcome" = c("failure", "cure"))
<- list(
visitcf_contrasts "v1cf" = c("v1failure", "v1cure"),
"v2cf" = c("v2failure", "v2cure"),
"v3cf" = c("v3failure", "v3cure"))
<- list(
visit_contrasts "v2v1" = c("c2", "c1"),
"v3v1" = c("c3", "c1"),
"v3v2" = c("c3", "c2"))
<- list(
visit_v1later "later_vs_first" = c("later", "first"))
<- list(
celltypes "eo_mono" = c("eosinophils", "monocytes"),
"ne_mono" = c("neutrophils", "monocytes"),
"eo_ne" = c("eosinophils", "neutrophils"))
<- list(
ethnicity_contrasts "mestizo_indigenous" = c("mestiza", "indigena"),
"mestizo_afrocol" = c("mestiza", "afrocol"),
"indigenous_afrocol" = c("indigena", "afrocol"))
Perform a svaseq-guided comparison of the two clinics. Ideally this will give some clue about just how strong the clinic-based batch effect really is and what its causes are.
<- tc_valid %>%
tc_clinic_type set_expt_conditions(fact = "clinic") %>%
set_expt_batches(fact = "typeofcells")
## The numbers of samples by condition are:
##
## Cali Tumaco
## 61 123
## The number of samples by batch are:
##
## biopsy eosinophils monocytes neutrophils
## 18 41 63 62
table(pData(tc_clinic_type)[["condition"]])
##
## Cali Tumaco
## 61 123
<- all_pairwise(tc_clinic_type, model_batch = "svaseq",
tc_all_clinic_de_sva filter = TRUE)
##
## Cali Tumaco
## 61 123
## Removing 0 low-count genes (14290 remaining).
## Setting 31271 low elements to zero.
## transform_counts: Found 31271 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_all_clinic_de_sva
## Error in eval(expr, envir, enclos): object 'tc_all_clinic_de_sva' not found
"deseq"]][["contrasts_performed"]] tc_all_clinic_de_sva[[
## Error in eval(expr, envir, enclos): object 'tc_all_clinic_de_sva' not found
<- combine_de_tables(
tc_all_clinic_table_sva keepers = clinic_contrasts,
tc_all_clinic_de_sva, # rda = glue("rda/tc_all_clinic_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/compare_clinics/tc_all_clinic_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/compare_clinics/tc_all_clinic_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_all_clinic_de_sva' not found
tc_all_clinic_table_sva
## Error in eval(expr, envir, enclos): object 'tc_all_clinic_table_sva' not found
<- extract_significant_genes(
tc_all_clinic_sig_sva
tc_all_clinic_table_sva,excel = glue("analyses/3_cali_and_tumaco/compare_clinics/tc_clinic_type_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/compare_clinics/tc_clinic_type_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_all_clinic_table_sva, excel = glue("analyses/3_cali_and_tumaco/compare_clinics/tc_clinic_type_sig_sva-v{ver}.xlsx")): object 'tc_all_clinic_table_sva' not found
tc_all_clinic_sig_sva
## Error in eval(expr, envir, enclos): object 'tc_all_clinic_sig_sva' not found
Let us take a quick look at the results of the comparison of Tumaco/Cali
Note: I keep re-introducing an error which causes these (volcano and MA) plots to be reversed with respect to the logFC values. Pay careful attention to these and make sure that they agree with the numbers of genes observed in the contrast.
## Check that up is up
summary(tc_all_clinic_table_sva[["data"]][["clinics"]][["deseq_logfc"]])
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'tc_all_clinic_table_sva' not found
## I think we can assume that most genes are down when considering Tumaco/Cali.
sum(tc_all_clinic_table_sva$data$clinics$deseq_logfc < -1.0 &
$data$clinics$deseq_adjp < 0.05) tc_all_clinic_table_sva
## Error in eval(expr, envir, enclos): object 'tc_all_clinic_table_sva' not found
"plots"]][["clinics"]][["deseq_vol_plots"]] tc_all_clinic_table_sva[[
## Error in eval(expr, envir, enclos): object 'tc_all_clinic_table_sva' not found
## Ok, so it says 1794 up, but that is clearly the down side... Something is definitely messed up.
## The points are on the correct sides of the plot, but the categories of up/down are reversed.
## Theresa noted that she colors differently, and I think better: left side gets called
## 'increased in denominator', right side gets called 'increased in numerator';
## these two groups are colored according to their condition colors, and everything else is gray.
## I am checking out Theresa's helper_functions.R to get a sense of how she handles this, I think
## I can use a variant of her idea pretty easily:
## 1. Add a column 'Significance', which is a factor, and contains either 'Not enriched',
## 'Enriched in x', or 'Enriched in y' according to the logfc/adjp.
## 2. use the significance column for the geom_point color/fill in the volcano plot.
## My change to this idea would be to extract the colors from the input expressionset.
<- simple_gprofiler(
increased_tumaco_categories "deseq"]][["ups"]][["clinics"]]) tc_all_clinic_sig_sva[[
## Error in "character" %in% class(sig_genes): object 'tc_all_clinic_sig_sva' not found
increased_tumaco_categories
## Error in eval(expr, envir, enclos): object 'increased_tumaco_categories' not found
"pvalue_plots"]][["BP"]] increased_tumaco_categories[[
## Error in eval(expr, envir, enclos): object 'increased_tumaco_categories' not found
<- simple_gprofiler(
increased_cali_categories "deseq"]][["downs"]][["clinics"]]) tc_all_clinic_sig_sva[[
## Error in "character" %in% class(sig_genes): object 'tc_all_clinic_sig_sva' not found
increased_cali_categories
## Error in eval(expr, envir, enclos): object 'increased_cali_categories' not found
"pvalue_plots"]][["BP"]] increased_cali_categories[[
## Error in eval(expr, envir, enclos): object 'increased_cali_categories' not found
There appear to be many more genes which are increased in the Tumaco samples with respect to the Cali samples.
The remaining cell types all have pretty strong clinic-based variance; but I am not certain if it is consistent across cell types.
table(pData(tc_eosinophils)[["condition"]])
##
## Cali_cure Tumaco_cure Tumaco_failure
## 15 17 9
<- all_pairwise(tc_eosinophils,
tc_eosinophils_clinic_de_nobatch model_batch = FALSE, filter = TRUE)
##
## Cali_cure Tumaco_cure Tumaco_failure
## 15 17 9
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_eosinophils_clinic_de_nobatch
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_clinic_de_nobatch' not found
"deseq"]][["contrasts_performed"]] tc_eosinophils_clinic_de_nobatch[[
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_clinic_de_nobatch' not found
<- combine_de_tables(
tc_eosinophils_clinic_table_nobatch keepers = tc_cf_contrasts,
tc_eosinophils_clinic_de_nobatch, # rda = glue("rda/tc_eosinophils_clinic_table_nobatch-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_table_nobatch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_table_nobatch-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_eosinophils_clinic_de_nobatch' not found
tc_eosinophils_clinic_table_nobatch
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_clinic_table_nobatch' not found
<- extract_significant_genes(
tc_eosinophils_clinic_sig_nobatch
tc_eosinophils_clinic_table_nobatch,excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_sig_nobatch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_sig_nobatch-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_eosinophils_clinic_table_nobatch, : object 'tc_eosinophils_clinic_table_nobatch' not found
tc_eosinophils_clinic_sig_nobatch
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_clinic_sig_nobatch' not found
<- all_pairwise(tc_eosinophils, model_batch = "svaseq", filter = TRUE) tc_eosinophils_clinic_de_sva
##
## Cali_cure Tumaco_cure Tumaco_failure
## 15 17 9
## Removing 0 low-count genes (10864 remaining).
## Setting 1043 low elements to zero.
## transform_counts: Found 1043 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_eosinophils_clinic_de_sva
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_clinic_de_sva' not found
"deseq"]][["contrasts_performed"]] tc_eosinophils_clinic_de_sva[[
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_clinic_de_sva' not found
<- combine_de_tables(
tc_eosinophils_clinic_table_sva keepers = tc_cf_contrasts,
tc_eosinophils_clinic_de_sva, # rda = glue("rda/tc_eosinophils_clinic_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_eosinophils_clinic_de_sva' not found
tc_eosinophils_clinic_table_sva
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_clinic_table_sva' not found
<- extract_significant_genes(
tc_eosinophils_clinic_sig_sva
tc_eosinophils_clinic_table_sva,excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_eosinophils_clinic_table_sva, excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Eosinophils/tc_eosinophils_clinic_sig_sva-v{ver}.xlsx")): object 'tc_eosinophils_clinic_table_sva' not found
tc_eosinophils_clinic_sig_sva
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_clinic_sig_sva' not found
Interestingly to me, the biopsy samples appear to have the least location-based variance. But we can perform an explicit DE and see how well that hypothesis holds up.
Note that these data include cure and fail samples for
table(pData(tc_biopsies)[["condition"]])
##
## Cali_cure Tumaco_cure Tumaco_failure
## 4 9 5
<- all_pairwise(tc_biopsies,
tc_biopsies_clinic_de_sva model_batch = "svaseq", filter = TRUE)
##
## Cali_cure Tumaco_cure Tumaco_failure
## 4 9 5
## Removing 0 low-count genes (13608 remaining).
## Setting 290 low elements to zero.
## transform_counts: Found 290 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_biopsies_clinic_de_sva
## Error in eval(expr, envir, enclos): object 'tc_biopsies_clinic_de_sva' not found
"deseq"]][["contrasts_performed"]] tc_biopsies_clinic_de_sva[[
## Error in eval(expr, envir, enclos): object 'tc_biopsies_clinic_de_sva' not found
<- combine_de_tables(
tc_biopsies_clinic_table_sva keepers = tc_cf_contrasts,
tc_biopsies_clinic_de_sva, # rda = glue("rda/tc_biopsies_clinic_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Biopsies/tc_biopsies_clinic_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Biopsies/tc_biopsies_clinic_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_biopsies_clinic_de_sva' not found
tc_biopsies_clinic_table_sva
## Error in eval(expr, envir, enclos): object 'tc_biopsies_clinic_table_sva' not found
<- extract_significant_genes(
tc_biopsies_clinic_sig_sva
tc_biopsies_clinic_table_sva,excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Biopsies/tc_biopsies_clinic_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Biopsies/tc_biopsies_clinic_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_biopsies_clinic_table_sva, excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Biopsies/tc_biopsies_clinic_sig_sva-v{ver}.xlsx")): object 'tc_biopsies_clinic_table_sva' not found
tc_biopsies_clinic_sig_sva
## Error in eval(expr, envir, enclos): object 'tc_biopsies_clinic_sig_sva' not found
At least for the moment, I am only looking at the differences between no-batch vs. sva across clinics for the monocyte samples. This was chosen mostly arbitrarily.
Our baseline is the comparison of the monocytes samples without batch in the model or surrogate estimation. In theory at least, this should correspond to the PCA plot above when no batch estimation was performed.
<- all_pairwise(tc_monocytes, model_batch = FALSE, filter = TRUE) tc_monocytes_de_nobatch
##
## Cali_cure Cali_failure Tumaco_cure Tumaco_failure
## 18 3 21 21
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_monocytes_de_nobatch
## Error in eval(expr, envir, enclos): object 'tc_monocytes_de_nobatch' not found
<- combine_de_tables(
tc_monocytes_table_nobatch keepers = clinic_cf_contrasts,
tc_monocytes_de_nobatch, # rda = glue("rda/tc_monocytes_clinic_table_nobatch-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_table_nobatch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_table_nobatch-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_monocytes_de_nobatch' not found
tc_monocytes_table_nobatch
## Error in eval(expr, envir, enclos): object 'tc_monocytes_table_nobatch' not found
<- extract_significant_genes(
tc_monocytes_sig_nobatch
tc_monocytes_table_nobatch,excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_sig_nobatch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_sig_nobatch-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_monocytes_table_nobatch, excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_sig_nobatch-v{ver}.xlsx")): object 'tc_monocytes_table_nobatch' not found
tc_monocytes_sig_nobatch
## Error in eval(expr, envir, enclos): object 'tc_monocytes_sig_nobatch' not found
In contrast, the following comparison should give a view of the data corresponding to the svaseq PCA plot above. In the best case scenario, we should therefore be able to see some significane differences between the Tumaco cure and fail samples.
<- all_pairwise(tc_monocytes, model_batch = "svaseq", filter = TRUE) tc_monocytes_de_sva
##
## Cali_cure Cali_failure Tumaco_cure Tumaco_failure
## 18 3 21 21
## Removing 0 low-count genes (11104 remaining).
## Setting 1447 low elements to zero.
## transform_counts: Found 1447 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_monocytes_de_sva
## Error in eval(expr, envir, enclos): object 'tc_monocytes_de_sva' not found
<- combine_de_tables(
tc_monocytes_table_sva keepers = clinic_cf_contrasts,
tc_monocytes_de_sva, # rda = glue("rda/tc_monocytes_clinic_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_monocytes_de_sva' not found
tc_monocytes_table_sva
## Error in eval(expr, envir, enclos): object 'tc_monocytes_table_sva' not found
<- extract_significant_genes(
tc_monocytes_sig_sva
tc_monocytes_table_sva,excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_monocytes_table_sva, excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Monocytes/tc_monocytes_clinic_sig_sva-v{ver}.xlsx")): object 'tc_monocytes_table_sva' not found
tc_monocytes_sig_sva
## Error in eval(expr, envir, enclos): object 'tc_monocytes_sig_sva' not found
The following block shows that these two results are exceedingly different, sugesting that the Cali cure/fail and Tumaco cure/fail cannot easily be considered in the same analysis. I did some playing around with my calculate_aucc function in this block and found that it is in some important way broken, at least if one expands the top-n genes to more than 20% of the number of genes in the data.
<- tc_monocytes_table_nobatch[["data"]][["cali"]] cali_table
## Error in eval(expr, envir, enclos): object 'tc_monocytes_table_nobatch' not found
<- tc_monocytes_table_nobatch[["data"]][["tumaco"]] table
## Error in eval(expr, envir, enclos): object 'tc_monocytes_table_nobatch' not found
<- calculate_aucc(cali_table, table, px = "deseq_adjp", py = "deseq_adjp",
cali_aucc lx = "deseq_logfc", ly = "deseq_logfc")
## Error in nrow(tbl): object 'cali_table' not found
cali_aucc
## Error in eval(expr, envir, enclos): object 'cali_aucc' not found
<- tc_monocytes_table_sva[["data"]][["cali"]] cali_table_sva
## Error in eval(expr, envir, enclos): object 'tc_monocytes_table_sva' not found
<- tc_monocytes_table_sva[["data"]][["tumaco"]] tumaco_table_sva
## Error in eval(expr, envir, enclos): object 'tc_monocytes_table_sva' not found
<- calculate_aucc(cali_table_sva, tumaco_table_sva, px = "deseq_adjp",
cali_aucc_sva py = "deseq_adjp", lx = "deseq_logfc", ly = "deseq_logfc")
## Error in nrow(tbl): object 'cali_table_sva' not found
cali_aucc_sva
## Error in eval(expr, envir, enclos): object 'cali_aucc_sva' not found
<- all_pairwise(tc_neutrophils,
tc_neutrophils_de_nobatch model_batch = FALSE, filter = TRUE)
##
## Cali_cure Cali_failure Tumaco_cure Tumaco_failure
## 18 3 20 21
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_neutrophils_de_nobatch
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_de_nobatch' not found
<- combine_de_tables(
tc_neutrophils_table_nobatch keepers = clinic_cf_contrasts,
tc_neutrophils_de_nobatch, # rda = glue("rda/tc_neutrophils_clinic_table_nobatch-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_table_nobatch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_table_nobatch-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_neutrophils_de_nobatch' not found
tc_neutrophils_table_nobatch
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_table_nobatch' not found
<- extract_significant_genes(
tc_neutrophils_sig_nobatch
tc_neutrophils_table_nobatch,excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_sig_nobatch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_sig_nobatch-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_neutrophils_table_nobatch, excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_sig_nobatch-v{ver}.xlsx")): object 'tc_neutrophils_table_nobatch' not found
tc_neutrophils_sig_nobatch
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_sig_nobatch' not found
<- all_pairwise(tc_neutrophils,
tc_neutrophils_de_sva model_batch = "svaseq", filter = TRUE)
##
## Cali_cure Cali_failure Tumaco_cure Tumaco_failure
## 18 3 20 21
## Removing 0 low-count genes (9242 remaining).
## Setting 1541 low elements to zero.
## transform_counts: Found 1541 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_neutrophils_de_sva
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_de_sva' not found
<- combine_de_tables(
tc_neutrophils_table_sva keepers = clinic_cf_contrasts,
tc_neutrophils_de_sva, # rda = glue("rda/tc_neutrophils_clinic_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_neutrophils_de_sva' not found
tc_neutrophils_table_sva
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_table_sva' not found
<- extract_significant_genes(
tc_neutrophils_sig_sva
tc_neutrophils_table_sva,excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_neutrophils_table_sva, excel = glue("analyses/3_cali_and_tumaco/clinic_cf/Neutrophils/tc_neutrophils_sig_sva-v{ver}.xlsx")): object 'tc_neutrophils_table_sva' not found
tc_neutrophils_sig_sva
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_sig_sva' not found
Given the above comparisons, we can extract some gene sets which resulted from those DE analyses and eventually perform some ontology/KEGG/reactome/etc searches. This reminds me, I want to make my extract_significant_ functions to return gene-set data structures and my various ontology searches to take them as inputs. This should help avoid potential errors when extracting up/down genes.
<- rownames(tc_all_clinic_sig_sva[["deseq"]][["ups"]][["clinics"]]) clinic_sigenes_up
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'tc_all_clinic_sig_sva' not found
<- rownames(tc_all_clinic_sig_sva[["deseq"]][["downs"]][["clinics"]]) clinic_sigenes_down
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'tc_all_clinic_sig_sva' not found
<- c(clinic_sigenes_up, clinic_sigenes_down) clinic_sigenes
## Error in eval(expr, envir, enclos): object 'clinic_sigenes_up' not found
<- rownames(tc_eosinophils_clinic_sig_sva[["deseq"]][["ups"]][["cure"]]) tc_eosinophils_sigenes_up
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'tc_eosinophils_clinic_sig_sva' not found
<- rownames(tc_eosinophils_clinic_sig_sva[["deseq"]][["downs"]][["cure"]]) tc_eosinophils_sigenes_down
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'tc_eosinophils_clinic_sig_sva' not found
<- rownames(tc_monocytes_sig_sva[["deseq"]][["ups"]][["cure"]]) tc_monocytes_sigenes_up
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'tc_monocytes_sig_sva' not found
<- rownames(tc_monocytes_sig_sva[["deseq"]][["downs"]][["cure"]]) tc_monocytes_sigenes_down
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'tc_monocytes_sig_sva' not found
<- rownames(tc_neutrophils_sig_sva[["deseq"]][["ups"]][["cure"]]) tc_neutrophils_sigenes_up
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'tc_neutrophils_sig_sva' not found
<- rownames(tc_neutrophils_sig_sva[["deseq"]][["downs"]][["cure"]]) tc_neutrophils_sigenes_down
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'tc_neutrophils_sig_sva' not found
<- c(tc_eosinophils_sigenes_up,
tc_eosinophils_sigenes tc_eosinophils_sigenes_down)
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_sigenes_up' not found
<- c(tc_monocytes_sigenes_up,
tc_monocytes_sigenes tc_monocytes_sigenes_down)
## Error in eval(expr, envir, enclos): object 'tc_monocytes_sigenes_up' not found
<- c(tc_neutrophils_sigenes_up,
tc_neutrophils_sigenes tc_neutrophils_sigenes_down)
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_sigenes_up' not found
In the following block, I am looking at the gProfiler over represented groups observed across clinics in only the Eosinophils. First I do so for all genes(up or down), followed by only the up and down groups. Each of the following will include only the Reactome and GO:BP plots. These searches did not have too many other hits, excepting the transcription factor database.
<- simple_gprofiler(tc_eosinophils_sigenes) tc_eosinophils_gp
## Error in "character" %in% class(sig_genes): object 'tc_eosinophils_sigenes' not found
tc_eosinophils_gp
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_gp' not found
$pvalue_plots$REAC tc_eosinophils_gp
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_gp' not found
$pvalue_plots$BP tc_eosinophils_gp
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_gp' not found
<- simple_gprofiler(tc_eosinophils_sigenes_up) tc_eosinophils_up_gp
## Error in "character" %in% class(sig_genes): object 'tc_eosinophils_sigenes_up' not found
tc_eosinophils_up_gp
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_up_gp' not found
$pvalue_plots$REAC tc_eosinophils_up_gp
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_up_gp' not found
<- simple_gprofiler(tc_eosinophils_sigenes_down) tc_eosinophils_down_gp
## Error in "character" %in% class(sig_genes): object 'tc_eosinophils_sigenes_down' not found
tc_eosinophils_down_gp
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_down_gp' not found
$pvalue_plots$REAC tc_eosinophils_down_gp
## Error in eval(expr, envir, enclos): object 'tc_eosinophils_down_gp' not found
In the following block I repeated the above query, but this time looking at the monocyte samples.
<- simple_gprofiler(tc_monocytes_sigenes) tc_monocytes_gp
## Error in "character" %in% class(sig_genes): object 'tc_monocytes_sigenes' not found
tc_monocytes_gp
## Error in eval(expr, envir, enclos): object 'tc_monocytes_gp' not found
$pvalue_plots$REAC tc_monocytes_gp
## Error in eval(expr, envir, enclos): object 'tc_monocytes_gp' not found
$pvalue_plots$BP tc_monocytes_gp
## Error in eval(expr, envir, enclos): object 'tc_monocytes_gp' not found
<- simple_gprofiler(tc_monocytes_sigenes_up) tc_monocytes_up_gp
## Error in "character" %in% class(sig_genes): object 'tc_monocytes_sigenes_up' not found
tc_monocytes_up_gp
## Error in eval(expr, envir, enclos): object 'tc_monocytes_up_gp' not found
$pvalue_plots$REAC tc_monocytes_up_gp
## Error in eval(expr, envir, enclos): object 'tc_monocytes_up_gp' not found
$pvalue_plots$BP tc_monocytes_up_gp
## Error in eval(expr, envir, enclos): object 'tc_monocytes_up_gp' not found
<- simple_gprofiler(tc_monocytes_sigenes_down) tc_monocytes_down_gp
## Error in "character" %in% class(sig_genes): object 'tc_monocytes_sigenes_down' not found
$pvalue_plots$REAC tc_monocytes_down_gp
## Error in eval(expr, envir, enclos): object 'tc_monocytes_down_gp' not found
$pvalue_plots$BP tc_monocytes_down_gp
## Error in eval(expr, envir, enclos): object 'tc_monocytes_down_gp' not found
Ibid. This time looking at the Neutrophils. Thus the first two images should be a superset of the second and third pairs of images; assuming that the genes in the up/down list do not cause the groups to no longer be significant. Interestingly, the reactome search did not return any hits for the increased search.
<- simple_gprofiler(tc_neutrophils_sigenes) tc_neutrophils_gp
## Error in "character" %in% class(sig_genes): object 'tc_neutrophils_sigenes' not found
## tc_neutrophils_gp$pvalue_plots$REAC ## no hits
$pvalue_plots$BP tc_neutrophils_gp
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_gp' not found
$pvalue_plots$TF tc_neutrophils_gp
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_gp' not found
<- simple_gprofiler(tc_neutrophils_sigenes_up) tc_neutrophils_up_gp
## Error in "character" %in% class(sig_genes): object 'tc_neutrophils_sigenes_up' not found
## tc_neutrophils_up_gp$pvalue_plots$REAC ## No hits
$pvalue_plots$BP tc_neutrophils_up_gp
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_up_gp' not found
<- simple_gprofiler(tc_neutrophils_sigenes_down) tc_neutrophils_down_gp
## Error in "character" %in% class(sig_genes): object 'tc_neutrophils_sigenes_down' not found
$pvalue_plots$REAC tc_neutrophils_down_gp
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_down_gp' not found
$pvalue_plots$BP tc_neutrophils_down_gp
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_down_gp' not found
The following expands the cross-clinic query above to also test the neutrophils. Once again, I think it will pretty strongly support the hypothesis that the two clinics are not compatible.
We are concerned that the clinic-based batch effect may make our results essentially useless. One way to test this concern is to compare the set of genes observed different between the Cali Cure/Fail vs. the Tumaco Cure/Fail.
<- tc_neutrophils_table_nobatch[["data"]][["cali"]] cali_table_nobatch
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_table_nobatch' not found
<- tc_neutrophils_table_nobatch[["data"]][["tumaco"]] tumaco_table_nobatch
## Error in eval(expr, envir, enclos): object 'tc_neutrophils_table_nobatch' not found
<- merge(cali_table_nobatch, tumaco_table_nobatch, by="row.names") cali_merged_nobatch
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'cali_table_nobatch' not found
cor.test(cali_merged_nobatch[, "deseq_logfc.x"], cali_merged_nobatch[, "deseq_logfc.y"])
## Error in cor.test(cali_merged_nobatch[, "deseq_logfc.x"], cali_merged_nobatch[, : object 'cali_merged_nobatch' not found
<- calculate_aucc(cali_table_nobatch, tumaco_table_nobatch, px = "deseq_adjp",
cali_aucc_nobatch py = "deseq_adjp", lx = "deseq_logfc", ly = "deseq_logfc")
## Error in nrow(tbl): object 'cali_table_nobatch' not found
$plot cali_aucc_nobatch
## Error in eval(expr, envir, enclos): object 'cali_aucc_nobatch' not found
Conversely, I can load some of the MsigDB categories from broad and perform a similar analysis using goseq to see if there are over represented categories.
<- load_gmt_signatures(signatures = "reference/msigdb/c7.all.v7.5.1.entrez.gmt",
broad_c7 signature_category = "c7")
<- load_gmt_signatures(signatures = "reference/msigdb/c2.all.v7.5.1.entrez.gmt",
broad_c2 signature_category = "c2")
<- load_gmt_signatures(signatures = "reference/msigdb/h.all.v7.5.1.entrez.gmt",
broad_h signature_category = "h")
<- goseq_msigdb(clinic_sigenes, length_db = hs_length,
clinic_gsea_msig_c2 signatures = broad_c2, signature_category = "c2")
## Error in "character" %in% class(sig_genes): object 'clinic_sigenes' not found
I was curious to try to understand why the two clinics appear to be so different vis a vis their PCA/DE; so I thought that gProfiler might help boil those results down to something more digestible.
Note that in the following block I used the function simple_gprofiler(), but later in this document I will use all_gprofiler(). The first invocation limits the search to a single table, while the second will iterate over every result in a pairwise differential expression analysis.
In this instance, we are looking at the vector of gene IDs deemed significantly different between the two clinics in either the up or down direction.
One other thing worth noting, the new version of gProfiler provides some fun interactive plots. I will add an example here.
<- simple_gprofiler(tc_eosinophils_sigenes_up) tc_eosinophil_gprofiler
## Error in "character" %in% class(sig_genes): object 'tc_eosinophils_sigenes_up' not found
tc_eosinophil_gprofiler
## Error in eval(expr, envir, enclos): object 'tc_eosinophil_gprofiler' not found
<- simple_gprofiler(clinic_sigenes) clinic_gp
## Error in "character" %in% class(sig_genes): object 'clinic_sigenes' not found
$pvalue_plots$REAC clinic_gp
## Error in eval(expr, envir, enclos): object 'clinic_gp' not found
$pvalue_plots$BP clinic_gp
## Error in eval(expr, envir, enclos): object 'clinic_gp' not found
$pvalue_plots$TF clinic_gp
## Error in eval(expr, envir, enclos): object 'clinic_gp' not found
$interactive_plots$GO clinic_gp
## Error in eval(expr, envir, enclos): object 'clinic_gp' not found
In all of the above, we are looking to understand the differences between the two location. Let us now step back and perform the original question: fail/cure without regard to location.
I performed this query with a few different parameters, notably with(out) sva and again using each cell type, including biopsies. The main reasion I am keeping these comparisons is in the relatively weak hope that there will be sufficient signal in the full dataset that it might be able to overcome the apparently ridiculous batch effect from the two clinics.
<- all_pairwise(tc_valid, filter = TRUE, model_batch = "svaseq") tc_all_cf_de_sva
##
## cure failure
## 122 62
## Removing 0 low-count genes (14290 remaining).
## Setting 27033 low elements to zero.
## transform_counts: Found 27033 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_all_cf_table_sva keepers = t_cf_contrast,
tc_all_cf_de_sva, # rda = glue("rda/tc_valid_cf_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_all_cf_de_sva' not found
<- extract_significant_genes(
tc_all_cf_sig_sva
tc_all_cf_table_sva,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_all_cf_table_sva, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_sig_sva-v{ver}.xlsx")): object 'tc_all_cf_table_sva' not found
<- all_pairwise(tc_valid, filter = TRUE, model_batch = TRUE) tc_all_cf_de_batch
##
## cure failure
## 122 62
##
## 1 2 3
## 83 50 51
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_all_cf_table_batch
tc_all_cf_de_batch,keepers = t_cf_contrast,
# rda = glue("rda/tc_valid_cf_table_batch-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_table_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_table_batch-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_all_cf_de_batch' not found
<- extract_significant_genes(
tc_all_cf_sig_batch
tc_all_cf_table_batch,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_sig_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_sig_batch-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_all_cf_table_batch, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_valid_cf_sig_batch-v{ver}.xlsx")): object 'tc_all_cf_table_batch' not found
In the following block, we repeat the same question, but using only the biopsy samples from both clinics.
<- set_expt_conditions(tc_biopsies, fact = "finaloutcome") tc_biopsies_cf
## The numbers of samples by condition are:
##
## cure failure
## 13 5
<- all_pairwise(tc_biopsies_cf, filter = TRUE, model_batch = "svaseq") tc_biopsies_cf_de_sva
##
## cure failure
## 13 5
## Removing 0 low-count genes (13608 remaining).
## Setting 222 low elements to zero.
## transform_counts: Found 222 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_biopsies_cf_table_sva keepers = t_cf_contrast,
tc_biopsies_cf_de_sva, # rda = glue("rda/tc_biopsies_cf_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/Biopsies/tc_biopsies_cf_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/Biopsies/tc_biopsies_cf_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_biopsies_cf_de_sva' not found
<- extract_significant_genes(
tc_biopsies_cf_sig_sva
tc_biopsies_cf_table_sva,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_biopsies_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_biopsies_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_biopsies_cf_table_sva, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_biopsies_cf_sig_sva-v{ver}.xlsx")): object 'tc_biopsies_cf_table_sva' not found
<- all_pairwise(tc_biopsies_cf, filter = TRUE, model_batch = TRUE) tc_biopsies_cf_de_batch
##
## cure failure
## 13 5
##
## 1
## 18
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_biopsies_cf_table_batch keepers = t_cf_contrast,
tc_biopsies_cf_de_batch, # rda = glue("rda/tc_biopsies_cf_table_batch-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_biopsies_cf_table_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_biopsies_cf_table_batch-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_biopsies_cf_de_batch' not found
<- extract_significant_genes(
tc_biopsies_cf_sig_batch
tc_biopsies_cf_table_batch,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_biopsies_cf_sig_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_biopsies_cf_sig_batch-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_biopsies_cf_table_batch, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_biopsies_cf_sig_batch-v{ver}.xlsx")): object 'tc_biopsies_cf_table_batch' not found
In the following block, we repeat the same question, but using only the Eosinophil samples from both clinics.
<- set_expt_conditions(tc_eosinophils, fact = "finaloutcome") tc_eosinophils_cf
## The numbers of samples by condition are:
##
## cure failure
## 32 9
<- all_pairwise(tc_eosinophils_cf, filter = TRUE, model_batch = "svaseq") tc_eosinophils_cf_de_sva
##
## cure failure
## 32 9
## Removing 0 low-count genes (10864 remaining).
## Setting 856 low elements to zero.
## transform_counts: Found 856 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_eosinophils_cf_table_sva keepers = t_cf_contrast,
tc_eosinophils_cf_de_sva, # rda = glue("rda/tc_eosinophils_cf_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/Eosinophils/tc_eosinophils_cf_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/Eosinophils/tc_eosinophils_cf_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_eosinophils_cf_de_sva' not found
<- extract_significant_genes(
tc_eosinophils_cf_sig_sva
tc_eosinophils_cf_table_sva,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_eosinophils_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_eosinophils_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_eosinophils_cf_table_sva, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_eosinophils_cf_sig_sva-v{ver}.xlsx")): object 'tc_eosinophils_cf_table_sva' not found
<- all_pairwise(tc_eosinophils_cf, filter = TRUE, model_batch = TRUE) tc_eosinophils_cf_de_batch
##
## cure failure
## 32 9
##
## 3 2 1
## 13 14 14
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_eosinophils_cf_table_batch keepers = t_cf_contrast,
tc_eosinophils_cf_de_batch, # rda = glue("rda/tc_eosinophils_cf_table_batch-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_eosinophils_cf_table_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_eosinophils_cf_table_batch-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_eosinophils_cf_de_batch' not found
<- extract_significant_genes(
tc_eosinophils_cf_sig_batch
tc_eosinophils_cf_table_batch,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_eosinophils_cf_sig_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_eosinophils_cf_sig_batch-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_eosinophils_cf_table_batch, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_eosinophils_cf_sig_batch-v{ver}.xlsx")): object 'tc_eosinophils_cf_table_batch' not found
Repeat yet again, this time with the monocyte samples. The idea is to see if there is a cell type which is particularly good (or bad) at discriminating the two clinics.
<- set_expt_conditions(tc_monocytes, fact = "finaloutcome") tc_monocytes_cf
## The numbers of samples by condition are:
##
## cure failure
## 39 24
<- all_pairwise(tc_monocytes_cf, filter = TRUE, model_batch = "svaseq") tc_monocytes_cf_de_sva
##
## cure failure
## 39 24
## Removing 0 low-count genes (11104 remaining).
## Setting 1326 low elements to zero.
## transform_counts: Found 1326 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_monocytes_cf_table_sva keepers = t_cf_contrast,
tc_monocytes_cf_de_sva, # rda = glue("rda/tc_monocytes_cf_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/Monocytes/tc_monocytes_cf_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/Monocytes/tc_monocytes_cf_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_monocytes_cf_de_sva' not found
<- extract_significant_genes(
tc_monocytes_cf_sig_sva
tc_monocytes_cf_table_sva,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_monocytes_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_monocytes_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_monocytes_cf_table_sva, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_monocytes_cf_sig_sva-v{ver}.xlsx")): object 'tc_monocytes_cf_table_sva' not found
<- all_pairwise(tc_monocytes_cf, filter = TRUE, model_batch = TRUE) tc_monocytes_cf_de_batch
##
## cure failure
## 39 24
##
## 3 2 1
## 19 18 26
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_monocytes_cf_table_batch keepers = t_cf_contrast,
tc_monocytes_cf_de_batch, # rda = glue("rda/tc_monocytes_cf_table_batch-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_monocytes_cf_table_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_monocytes_cf_table_batch-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_monocytes_cf_de_batch' not found
<- extract_significant_genes(
tc_monocytes_cf_sig_batch
tc_monocytes_cf_table_batch,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_monocytes_cf_sig_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_monocytes_cf_sig_batch-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_monocytes_cf_table_batch, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_monocytes_cf_sig_batch-v{ver}.xlsx")): object 'tc_monocytes_cf_table_batch' not found
Last try, this time using the Neutrophil samples.
<- set_expt_conditions(tc_neutrophils, fact = "finaloutcome") tc_neutrophils_cf
## The numbers of samples by condition are:
##
## cure failure
## 38 24
<- all_pairwise(tc_neutrophils_cf,
tc_neutrophils_cf_de_sva filter = TRUE, model_batch = "svaseq")
##
## cure failure
## 38 24
## Removing 0 low-count genes (9242 remaining).
## Setting 1562 low elements to zero.
## transform_counts: Found 1562 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_neutrophils_cf_table_sva keepers = t_cf_contrast,
tc_neutrophils_cf_de_sva, # rda = glue("rda/tc_neutrophils_cf_table_sva-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/Neutrophils/tc_neutrophils_cf_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/Neutrophils/tc_neutrophils_cf_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_neutrophils_cf_de_sva' not found
<- extract_significant_genes(
tc_neutrophils_cf_sig_sva
tc_neutrophils_cf_table_sva,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_neutrophils_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_neutrophils_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_neutrophils_cf_table_sva, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_neutrophils_cf_sig_sva-v{ver}.xlsx")): object 'tc_neutrophils_cf_table_sva' not found
<- all_pairwise(tc_neutrophils_cf, filter = TRUE, model_batch = TRUE) tc_neutrophils_cf_de_batch
##
## cure failure
## 38 24
##
## 3 2 1
## 19 18 25
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_neutrophils_cf_table_batch keepers = t_cf_contrast,
tc_neutrophils_cf_de_batch, # rda = glue("rda/tc_neutrophils_cf_table_batch-v{ver}.rda"),
excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_neutrophils_cf_table_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_neutrophils_cf_table_batch-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_neutrophils_cf_de_batch' not found
<- extract_significant_genes(
tc_neutrophils_cf_sig_batch
tc_neutrophils_cf_table_batch,excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_neutrophils_cf_sig_batch-v{ver}.xlsx"))
## Deleting the file analyses/3_cali_and_tumaco/cf/All_Samples/tc_neutrophils_cf_sig_batch-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_neutrophils_cf_table_batch, excel = glue("analyses/3_cali_and_tumaco/cf/All_Samples/tc_neutrophils_cf_sig_batch-v{ver}.xlsx")): object 'tc_neutrophils_cf_table_batch' not found
Start over, this time with only the samples from Tumaco. We currently are assuming these will prove to be the only analyses used for final interpretation. This is primarily because we have insufficient failed treatment samples from Cali.
<- "analyses/4_tumaco/DE_Cure_vs_Fail" xlsx_prefix
Start by considering all Tumaco cell types. Note that in this case we only use SVA, primarily because I am not certain what would be an appropriate batch factor, perhaps visit?
<- all_pairwise(t_clinical, model_batch = "svaseq", filter = TRUE) t_cf_clinical_de_sva
##
## cure failure
## 67 56
## Removing 0 low-count genes (14149 remaining).
## Setting 17282 low elements to zero.
## transform_counts: Found 17282 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
t_cf_clinical_de_sva
## Error in eval(expr, envir, enclos): object 't_cf_clinical_de_sva' not found
<- combine_de_tables(
t_cf_clinical_table_sva keepers = t_cf_contrast,
t_cf_clinical_de_sva, # rda = glue("rda/t_clinical_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/All_Samples/t_clinical_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/All_Samples/t_clinical_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_clinical_de_sva' not found
t_cf_clinical_table_sva
## Error in eval(expr, envir, enclos): object 't_cf_clinical_table_sva' not found
"plots"]][["outcome"]][["deseq_ma_plots"]] t_cf_clinical_table_sva[[
## Error in eval(expr, envir, enclos): object 't_cf_clinical_table_sva' not found
<- extract_significant_genes(
t_cf_clinical_sig_sva
t_cf_clinical_table_sva,excel = glue("{xlsx_prefix}/All_Samples/t_clinical_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/All_Samples/t_clinical_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_clinical_table_sva, excel = glue("{xlsx_prefix}/All_Samples/t_clinical_cf_sig_sva-v{ver}.xlsx")): object 't_cf_clinical_table_sva' not found
t_cf_clinical_sig_sva
## Error in eval(expr, envir, enclos): object 't_cf_clinical_sig_sva' not found
dim(t_cf_clinical_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_sig_sva' not found
dim(t_cf_clinical_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_sig_sva' not found
The following gProfiler searches use the all_gprofiler() function instead of simple_gprofiler(). As a result, the results are separated by {contrast}_{direction}. Thus ‘outcome_down’.
The same plots are available as the previous gProfiler searches, but in many of the following runs, I used the dotplot() function to get a slightly different view of the results.
<- all_gprofiler(t_cf_clinical_sig_sva) t_cf_clinical_gp
## Error in all_gprofiler(t_cf_clinical_sig_sva): object 't_cf_clinical_sig_sva' not found
## Wikipathways of the up c/f genes
::dotplot(t_cf_clinical_gp[["outcome_up"]][["WP_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_gp' not found
## Transcription factor database of the up c/f genes
::dotplot(t_cf_clinical_gp[["outcome_up"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_gp' not found
## Reactome of the up c/f genes
::dotplot(t_cf_clinical_gp[["outcome_up"]][["REAC_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_gp' not found
## GO of the down c/f genes
::dotplot(t_cf_clinical_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_gp' not found
"outcome_up"]][["pvalue_plots"]][["BP"]] t_cf_clinical_gp[[
## Error in eval(expr, envir, enclos): object 't_cf_clinical_gp' not found
## Reactome of the down c/f genes
::dotplot(t_cf_clinical_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_gp' not found
::dotplot(t_cf_clinical_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_gp' not found
Later in this document I do a bunch of visit/cf comparisons. In this block I want to explicitly only compare v1 to other visits. This is something I did quite a lot in the 2019 datasets, but never actually moved to this document.
<- all_pairwise(tc_v1vs, model_batch = "svaseq", filter = TRUE) v1_vs_later
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'tc_v1vs' not found
<- combine_de_tables(
v1_vs_later_table keepers = visit_v1later,
v1_vs_later, excel = glue("excel/v1_vs_later_tables-v{ver}.xlsx"))
## Error in get_expt_colors(apr[["input"]]): object 'v1_vs_later' not found
<- extract_significant_genes(
v1_vs_later_sig
v1_vs_later_table,excel = glue("excel/v1_vs_later_sig-v{ver}.xlsx"))
## Error in extract_significant_genes(v1_vs_later_table, excel = glue("excel/v1_vs_later_sig-v{ver}.xlsx")): object 'v1_vs_later_table' not found
<- all_gprofiler(v1_vs_later_sig) v1later_gp
## Error in all_gprofiler(v1_vs_later_sig): object 'v1_vs_later_sig' not found
1]]$pvalue_plots$REAC v1later_gp[[
## Error in eval(expr, envir, enclos): object 'v1later_gp' not found
2]]$pvalue_plots$REAC v1later_gp[[
## Error in eval(expr, envir, enclos): object 'v1later_gp' not found
<- all_pairwise(t_v1vs, model_batch = "svaseq", filter = TRUE) tv1_vs_later
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 't_v1vs' not found
<- combine_de_tables(
tv1_vs_later_table keepers = visit_v1later,
tv1_vs_later, excel = glue("excel/tv1_vs_later_tables-v{ver}.xlsx"))
## Error in get_expt_colors(apr[["input"]]): object 'tv1_vs_later' not found
<- extract_significant_genes(
tv1_vs_later_sig
tv1_vs_later_table,excel = glue("excel/tv1_vs_later_sig-v{ver}.xlsx"))
## Error in extract_significant_genes(tv1_vs_later_table, excel = glue("excel/tv1_vs_later_sig-v{ver}.xlsx")): object 'tv1_vs_later_table' not found
<- all_gprofiler(v1_vs_later_sig) v1later_gp
## Error in all_gprofiler(v1_vs_later_sig): object 'v1_vs_later_sig' not found
1]]$pvalue_plots$REAC v1later_gp[[
## Error in eval(expr, envir, enclos): object 'v1later_gp' not found
2]]$pvalue_plots$REAC v1later_gp[[
## Error in eval(expr, envir, enclos): object 'v1later_gp' not found
<- all_gprofiler(tv1_vs_later_sig) tv1later_gp
## Error in all_gprofiler(tv1_vs_later_sig): object 'tv1_vs_later_sig' not found
1]]$pvalue_plots$BP tv1later_gp[[
## Error in eval(expr, envir, enclos): object 'tv1later_gp' not found
2]]$pvalue_plots$BP tv1later_gp[[
## Error in eval(expr, envir, enclos): object 'tv1later_gp' not found
<- all_pairwise(tc_sex, model_batch = "svaseq", filter = TRUE) tc_sex_de
##
## female male
## 28 156
## Removing 0 low-count genes (14290 remaining).
## Setting 26263 low elements to zero.
## transform_counts: Found 26263 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
tc_sex_table excel = glue("excel/tc_sex_table-v{ver}.xlsx")) tc_sex_de,
## Deleting the file excel/tc_sex_table-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_sex_de' not found
<- extract_significant_genes(
tc_sex_sig excel = glue("excel/tc_sex_sig-v{ver}.xlsx")) tc_sex_table,
## Deleting the file excel/tc_sex_sig-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_sex_table, excel = glue("excel/tc_sex_sig-v{ver}.xlsx")): object 'tc_sex_table' not found
<- all_gprofiler(tc_sex_sig) tc_sex_gp
## Error in all_gprofiler(tc_sex_sig): object 'tc_sex_sig' not found
<- subset_expt(tc_sex, subset = "clinic == 'Tumaco'") t_sex
## subset_expt(): There were 184, now there are 123 samples.
<- all_pairwise(t_sex, model_batch = "svaseq", filter = TRUE) t_sex_de
##
## female male
## 22 101
## Removing 0 low-count genes (14149 remaining).
## Setting 17259 low elements to zero.
## transform_counts: Found 17259 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_sex_table excel = glue("excel/t_sex_table-v{ver}.xlsx")) t_sex_de,
## Deleting the file excel/t_sex_table-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_sex_de' not found
<- extract_significant_genes(
t_sex_sig excel = glue("excel/t_sex_sig-v{ver}.xlsx")) t_sex_table,
## Deleting the file excel/t_sex_sig-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_sex_table, excel = glue("excel/t_sex_sig-v{ver}.xlsx")): object 't_sex_table' not found
<- all_gprofiler(t_sex_sig) t_sex_gp
## Error in all_gprofiler(t_sex_sig): object 't_sex_sig' not found
<- subset_expt(tc_sex, subset = "finaloutcome=='cure'") tc_sex_cure
## subset_expt(): There were 184, now there are 122 samples.
<- all_pairwise(tc_sex_cure, model_batch = "svaseq", filter = TRUE) tc_sex_cure_de
##
## female male
## 19 103
## Removing 0 low-count genes (14149 remaining).
## Setting 16962 low elements to zero.
## transform_counts: Found 16962 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
tc_sex_cure_de
## Error in eval(expr, envir, enclos): object 'tc_sex_cure_de' not found
<- combine_de_tables(
tc_sex_cure_table excel = glue("excel/tc_sex_cure_table-v{ver}.xlsx")) tc_sex_cure_de,
## Deleting the file excel/tc_sex_cure_table-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'tc_sex_cure_de' not found
tc_sex_cure_table
## Error in eval(expr, envir, enclos): object 'tc_sex_cure_table' not found
<- extract_significant_genes(
tc_sex_cure_sig excel = glue("excel/tc_sex_cure_sig-v{ver}.xlsx")) tc_sex_cure_table,
## Deleting the file excel/tc_sex_cure_sig-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(tc_sex_cure_table, excel = glue("excel/tc_sex_cure_sig-v{ver}.xlsx")): object 'tc_sex_cure_table' not found
tc_sex_cure_sig
## Error in eval(expr, envir, enclos): object 'tc_sex_cure_sig' not found
<- all_gprofiler(tc_sex_cure_sig) tc_sex_cure_gp
## Error in all_gprofiler(tc_sex_cure_sig): object 'tc_sex_cure_sig' not found
tc_sex_cure_gp
## Error in eval(expr, envir, enclos): object 'tc_sex_cure_gp' not found
1]][["pvalue_plots"]][["BP"]] tc_sex_cure_gp[[
## Error in eval(expr, envir, enclos): object 'tc_sex_cure_gp' not found
2]][["pvalue_plots"]][["BP"]] tc_sex_cure_gp[[
## Error in eval(expr, envir, enclos): object 'tc_sex_cure_gp' not found
<- subset_expt(tc_sex_cure, subset = "clinic == 'Tumaco'") t_sex_cure
## subset_expt(): There were 122, now there are 67 samples.
<- all_pairwise(t_sex_cure, model_batch = "svaseq", filter = TRUE) t_sex_cure_de
##
## female male
## 13 54
## Removing 0 low-count genes (13964 remaining).
## Setting 8959 low elements to zero.
## transform_counts: Found 8959 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
t_sex_cure_de
## Error in eval(expr, envir, enclos): object 't_sex_cure_de' not found
<- combine_de_tables(
t_sex_cure_table excel = glue("excel/t_sex_cure_table-v{ver}.xlsx")) t_sex_cure_de,
## Deleting the file excel/t_sex_cure_table-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_sex_cure_de' not found
t_sex_cure_table
## Error in eval(expr, envir, enclos): object 't_sex_cure_table' not found
<- extract_significant_genes(
t_sex_cure_sig excel = glue("excel/t_sex_cure_sig-v{ver}.xlsx")) t_sex_cure_table,
## Deleting the file excel/t_sex_cure_sig-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_sex_cure_table, excel = glue("excel/t_sex_cure_sig-v{ver}.xlsx")): object 't_sex_cure_table' not found
t_sex_cure_sig
## Error in eval(expr, envir, enclos): object 't_sex_cure_sig' not found
<- all_gprofiler(t_sex_cure_sig) t_sex_cure_gp
## Error in all_gprofiler(t_sex_cure_sig): object 't_sex_cure_sig' not found
t_sex_cure_gp
## Error in eval(expr, envir, enclos): object 't_sex_cure_gp' not found
1]][["pvalue_plots"]][["BP"]] tc_sex_cure_gp[[
## Error in eval(expr, envir, enclos): object 'tc_sex_cure_gp' not found
<- all_pairwise(tc_etnia_expt, model_batch = "svaseq", filter = TRUE) tc_ethnicity_de
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'tc_etnia_expt' not found
tc_ethnicity_de
## Error in eval(expr, envir, enclos): object 'tc_ethnicity_de' not found
<- combine_de_tables(
tc_ethnicity_table keepers = ethnicity_contrasts,
tc_ethnicity_de, excel = glue("excel/tc_ethnicity_table-v{ver}.xlsx"))
## Error in get_expt_colors(apr[["input"]]): object 'tc_ethnicity_de' not found
tc_ethnicity_table
## Error in eval(expr, envir, enclos): object 'tc_ethnicity_table' not found
"plots"]][["mestizo_indigenous"]][["deseq_ma_plots"]] tc_ethnicity_table[[
## Error in eval(expr, envir, enclos): object 'tc_ethnicity_table' not found
"plots"]][["mestizo_afrocol"]][["deseq_ma_plots"]] tc_ethnicity_table[[
## Error in eval(expr, envir, enclos): object 'tc_ethnicity_table' not found
"plots"]][["indigenous_afrocol"]][["deseq_ma_plots"]] tc_ethnicity_table[[
## Error in eval(expr, envir, enclos): object 'tc_ethnicity_table' not found
<- extract_significant_genes(
tc_ethnicity_sig excel = glue("excel/tc_ethnicity_sig-v{ver}.xlsx")) tc_ethnicity_table,
## Error in extract_significant_genes(tc_ethnicity_table, excel = glue("excel/tc_ethnicity_sig-v{ver}.xlsx")): object 'tc_ethnicity_table' not found
<- all_gprofiler(tc_ethnicity_sig) tc_ethnicity_gp
## Error in all_gprofiler(tc_ethnicity_sig): object 'tc_ethnicity_sig' not found
<- all_pairwise(t_etnia_expt, model_batch = "svaseq", filter = TRUE) t_ethnicity_de
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 't_etnia_expt' not found
<- combine_de_tables(
t_ethnicity_table excel = glue("excel/t_ethnicity_table-v{ver}.xlsx")) t_ethnicity_de,
## Error in get_expt_colors(apr[["input"]]): object 't_ethnicity_de' not found
<- extract_significant_genes(
t_ethnicity_sig excel = glue("excel/t_ethnicity_sig-v{ver}.xlsx")) t_ethnicity_table,
## Error in extract_significant_genes(t_ethnicity_table, excel = glue("excel/t_ethnicity_sig-v{ver}.xlsx")): object 't_ethnicity_table' not found
<- all_gprofiler(t_ethnicity_sig) t_ethnicity_gp
## Error in all_gprofiler(t_ethnicity_sig): object 't_ethnicity_sig' not found
<- subset_expt(tc_etnia_expt, subset = "finaloutcome=='cure'") ethnicity_cure
## Error in h(simpleError(msg, call)): error in evaluating the argument 'expt' in selecting a method for function 'subset_expt': object 'tc_etnia_expt' not found
<- all_pairwise(ethnicity_cure, model_batch = "svaseq", filter = TRUE) ethnicity_cure_de
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'ethnicity_cure' not found
<- combine_de_tables(
ethnicity_cure_table keepers = ethnicity_contrasts,
ethnicity_cure_de, excel = glue("excel/ethnicity_cure_table-v{ver}.xlsx"))
## Error in get_expt_colors(apr[["input"]]): object 'ethnicity_cure_de' not found
ethnicity_cure_table
## Error in eval(expr, envir, enclos): object 'ethnicity_cure_table' not found
"plots"]][["mestizo_indigenous"]][["deseq_ma_plots"]] ethnicity_cure_table[[
## Error in eval(expr, envir, enclos): object 'ethnicity_cure_table' not found
"plots"]][["mestizo_afrocol"]][["deseq_ma_plots"]] ethnicity_cure_table[[
## Error in eval(expr, envir, enclos): object 'ethnicity_cure_table' not found
"plots"]][["indigenous_afrocol"]][["deseq_ma_plots"]] ethnicity_cure_table[[
## Error in eval(expr, envir, enclos): object 'ethnicity_cure_table' not found
<- extract_significant_genes(
ethnicity_cure_sig excel = glue("excel/ethnicity_cure_sig-v{ver}.xlsx")) ethnicity_cure_table,
## Error in extract_significant_genes(ethnicity_cure_table, excel = glue("excel/ethnicity_cure_sig-v{ver}.xlsx")): object 'ethnicity_cure_table' not found
ethnicity_cure_sig
## Error in eval(expr, envir, enclos): object 'ethnicity_cure_sig' not found
<- all_gprofiler(ethnicity_cure_sig) ethnicity_cure_gp
## Error in all_gprofiler(ethnicity_cure_sig): object 'ethnicity_cure_sig' not found
ethnicity_cure_gp
## Error in eval(expr, envir, enclos): object 'ethnicity_cure_gp' not found
"indigenous_afrocol_down"]][["pvalue_plots"]][["MF"]] ethnicity_cure_gp[[
## Error in eval(expr, envir, enclos): object 'ethnicity_cure_gp' not found
"mestizo_afrocol_down"]][["pvalue_plots"]][["MF"]] ethnicity_cure_gp[[
## Error in eval(expr, envir, enclos): object 'ethnicity_cure_gp' not found
One of the most compelling ideas in the data is the opportunity to find genes in the first visit which may help predict the likelihood that a person will respond well to treatment. The following block will therefore look at cure/fail from Tumaco at visit 1.
<- all_pairwise(tv1_samples, model_batch = "svaseq", filter = TRUE) t_cf_clinical_v1_de_sva
##
## cure failure
## 30 24
## Removing 0 low-count genes (14016 remaining).
## Setting 7615 low elements to zero.
## transform_counts: Found 7615 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
t_cf_clinical_v1_de_sva
## Error in eval(expr, envir, enclos): object 't_cf_clinical_v1_de_sva' not found
<- combine_de_tables(
t_cf_clinical_v1_table_sva keepers = t_cf_contrast,
t_cf_clinical_v1_de_sva, # rda = glue("rda/t_clinical_v1_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v1_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/All_Samples/t_clinical_v1_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_clinical_v1_de_sva' not found
t_cf_clinical_v1_table_sva
## Error in eval(expr, envir, enclos): object 't_cf_clinical_v1_table_sva' not found
<- extract_significant_genes(
t_cf_clinical_v1_sig_sva
t_cf_clinical_v1_table_sva,excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v1_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/All_Samples/t_clinical_v1_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_clinical_v1_table_sva, excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v1_cf_sig_sva-v{ver}.xlsx")): object 't_cf_clinical_v1_table_sva' not found
dim(t_cf_clinical_v1_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_v1_sig_sva' not found
dim(t_cf_clinical_v1_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_v1_sig_sva' not found
The visit 2 and visit 3 samples are interesting because they provide an opportunity to see if we can observe changes in response in the middle and end of treatment…
<- all_pairwise(tv2_samples, model_batch = "svaseq", filter = TRUE) t_cf_clinical_v2_de_sva
##
## cure failure
## 20 15
## Removing 0 low-count genes (11559 remaining).
## Setting 2848 low elements to zero.
## transform_counts: Found 2848 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_clinical_v2_table_sva keepers = t_cf_contrast,
t_cf_clinical_v2_de_sva, # rda = glue("rda/t_clinical_v2_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v2_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/All_Samples/t_clinical_v2_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_clinical_v2_de_sva' not found
<- extract_significant_genes(
t_cf_clinical_v2_sig_sva
t_cf_clinical_v2_table_sva,excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v2_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/All_Samples/t_clinical_v2_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_clinical_v2_table_sva, excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v2_cf_sig_sva-v{ver}.xlsx")): object 't_cf_clinical_v2_table_sva' not found
dim(t_cf_clinical_v2_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_v2_sig_sva' not found
dim(t_cf_clinical_v2_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_v2_sig_sva' not found
<- all_pairwise(tv3_samples, model_batch = "svaseq", filter = TRUE) t_cf_clinical_v3_de_sva
##
## cure failure
## 17 17
## Removing 0 low-count genes (11449 remaining).
## Setting 1878 low elements to zero.
## transform_counts: Found 1878 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_clinical_v3_table_sva keepers = t_cf_contrast,
t_cf_clinical_v3_de_sva, # rda = glue("rda/t_clinical_v3_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v3_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/All_Samples/t_clinical_v3_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_clinical_v3_de_sva' not found
<- extract_significant_genes(
t_cf_clinical_v3_sig_sva
t_cf_clinical_v3_table_sva,excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v3_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/All_Samples/t_clinical_v3_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_clinical_v3_table_sva, excel = glue("{xlsx_prefix}/All_Samples/t_clinical_v3_cf_sig_sva-v{ver}.xlsx")): object 't_cf_clinical_v3_table_sva' not found
dim(t_cf_clinical_v3_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_v3_sig_sva' not found
dim(t_cf_clinical_v3_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_v3_sig_sva' not found
It looks like there are very few groups in the visit 1 significant genes.
<- all_gprofiler(t_cf_clinical_v1_sig_sva) t_cf_clinical_v1_sig_sva_gp
## Error in all_gprofiler(t_cf_clinical_v1_sig_sva): object 't_cf_clinical_v1_sig_sva' not found
## Wikipathways of the up c/f genes
::dotplot(t_cf_clinical_v1_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v1_sig_sva_gp' not found
::dotplot(t_cf_clinical_v1_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v1_sig_sva_gp' not found
Up: 74 GO, 4 KEGG, 6 reactome, 4 WP, 56 TF, 1 miRNA, 0 HP/HPA/CORUM. Down: 19 GO, 1 KEGG, 1 HP, 2 HPA, 0 reactome/wp/tf/corum
<- all_gprofiler(t_cf_clinical_v2_sig_sva) t_cf_clinical_v2_sig_sva_gp
## Error in all_gprofiler(t_cf_clinical_v2_sig_sva): object 't_cf_clinical_v2_sig_sva' not found
## Wikipathways of the up c/f genes
::dotplot(t_cf_clinical_v2_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v2_sig_sva_gp' not found
::dotplot(t_cf_clinical_v2_sig_sva_gp[["outcome_up"]][["REAC_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v2_sig_sva_gp' not found
::dotplot(t_cf_clinical_v2_sig_sva_gp[["outcome_up"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v2_sig_sva_gp' not found
::dotplot(t_cf_clinical_v2_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v2_sig_sva_gp' not found
Up: 120 genes; 141 GO, 1 KEGG, 5 Reactome, 2 WP, 30 TF, 1 miRNA, 0 HPA/CORUM/HP Down: 62 genes; 30 GO, 2 KEGG, 1 Reactome, 0 WP/TF/miRNA/HPA/CORUM/HP,
<- all_gprofiler(t_cf_clinical_v3_sig_sva) t_cf_clinical_v3_sig_sva_gp
## Error in all_gprofiler(t_cf_clinical_v3_sig_sva): object 't_cf_clinical_v3_sig_sva' not found
## Wikipathways of the up c/f genes
::dotplot(t_cf_clinical_v3_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v3_sig_sva_gp' not found
::dotplot(t_cf_clinical_v3_sig_sva_gp[["outcome_up"]][["REAC_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v3_sig_sva_gp' not found
::dotplot(t_cf_clinical_v3_sig_sva_gp[["outcome_up"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v3_sig_sva_gp' not found
::dotplot(t_cf_clinical_v3_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_v3_sig_sva_gp' not found
The biopsy samples are problematic for a few reasons, so let us repeat without them.
<- all_pairwise(t_clinical_nobiop,
t_cf_clinical_nobiop_de_sva model_batch = "svaseq", filter = TRUE)
##
## cure failure
## 58 51
## Removing 0 low-count genes (11907 remaining).
## Setting 9578 low elements to zero.
## transform_counts: Found 9578 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_clinical_nobiop_table_sva keepers = t_cf_contrast,
t_cf_clinical_nobiop_de_sva, # rda = glue("rda/t_clinical_nobiop_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/No_Biopsies/t_clinical_nobiop_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/No_Biopsies/t_clinical_nobiop_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_clinical_nobiop_de_sva' not found
<- extract_significant_genes(
t_cf_clinical_nobiop_sig_sva
t_cf_clinical_nobiop_table_sva,excel = glue("{xlsx_prefix}/No_Biopsies/t_clinical_nobiop_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/No_Biopsies/t_clinical_nobiop_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_clinical_nobiop_table_sva, excel = glue("{xlsx_prefix}/No_Biopsies/t_clinical_nobiop_cf_sig_sva-v{ver}.xlsx")): object 't_cf_clinical_nobiop_table_sva' not found
dim(t_cf_clinical_nobiop_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_nobiop_sig_sva' not found
dim(t_cf_clinical_nobiop_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_clinical_nobiop_sig_sva' not found
Up: 137 genes; 88 GO, 0 KEGG, 6 Reactome, 1 WP, 46 TF, 1 miRNA, 0 others Down: 73 genes; 78 GO, 1 KEGG, 1 Reactome, 9 TF, 0 others
<- all_gprofiler(t_cf_clinical_nobiop_sig_sva) t_cf_clinical_nobiop_sig_sva_gp
## Error in all_gprofiler(t_cf_clinical_nobiop_sig_sva): object 't_cf_clinical_nobiop_sig_sva' not found
::dotplot(t_cf_clinical_nobiop_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_nobiop_sig_sva_gp' not found
::dotplot(t_cf_clinical_nobiop_sig_sva_gp[["outcome_up"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_nobiop_sig_sva_gp' not found
::dotplot(t_cf_clinical_nobiop_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_clinical_nobiop_sig_sva_gp' not found
Now let us switch our view to each individual cell type collected. The hope here is that we will be able to learn some cell-specific differences in the response for people who did(not) respond well.
<- all_pairwise(t_biopsies, model_batch = "svaseq", filter = TRUE) t_cf_biopsy_de_sva
##
## Tumaco_cure Tumaco_failure
## 9 5
## Removing 0 low-count genes (13506 remaining).
## Setting 145 low elements to zero.
## transform_counts: Found 145 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_biopsy_table_sva keepers = cf_contrast,
t_cf_biopsy_de_sva, # rda = glue("rda/t_biopsy_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Biopsies/t_biopsy_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Biopsies/t_biopsy_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_biopsy_de_sva' not found
<- extract_significant_genes(
t_cf_biopsy_sig_sva
t_cf_biopsy_table_sva,excel = glue("{xlsx_prefix}/Biopsies/t_cf_biopsy_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Biopsies/t_cf_biopsy_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_biopsy_table_sva, excel = glue("{xlsx_prefix}/Biopsies/t_cf_biopsy_sig_sva-v{ver}.xlsx")): object 't_cf_biopsy_table_sva' not found
dim(t_cf_biopsy_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_biopsy_sig_sva' not found
dim(t_cf_biopsy_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_biopsy_sig_sva' not found
Up: 17 genes; 74 GO, 3 KEGG, 1 Reactome, 3 WP, 1 TF, 0 others Down: 11 genes; 2 GO, 0 others
<- all_gprofiler(t_cf_biopsy_sig_sva) t_cf_biopsy_sig_sva_gp
## Error in all_gprofiler(t_cf_biopsy_sig_sva): object 't_cf_biopsy_sig_sva' not found
::dotplot(t_cf_biopsy_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_biopsy_sig_sva_gp' not found
::dotplot(t_cf_biopsy_sig_sva_gp[["outcome_up"]][["WP_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_biopsy_sig_sva_gp' not found
::dotplot(t_cf_biopsy_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_biopsy_sig_sva_gp' not found
Same question, but this time looking at monocytes. In addition, this comparison was done twice, once using SVA and once using visit as a batch factor.
<- all_pairwise(t_monocytes, model_batch = "svaseq",
t_cf_monocyte_de_sva filter = TRUE)
##
## Tumaco_cure Tumaco_failure
## 21 21
## Removing 0 low-count genes (10859 remaining).
## Setting 730 low elements to zero.
## transform_counts: Found 730 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_monocyte_tables_sva keepers = cf_contrast,
t_cf_monocyte_de_sva, # rda = glue("rda/t_monocyte_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_monocyte_de_sva' not found
<- extract_significant_genes(
t_cf_monocyte_sig_sva
t_cf_monocyte_tables_sva,excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_monocyte_tables_sva, excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_cf_sig_sva-v{ver}.xlsx")): object 't_cf_monocyte_tables_sva' not found
dim(t_cf_monocyte_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_sig_sva' not found
dim(t_cf_monocyte_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_sig_sva' not found
<- all_pairwise(t_monocytes, model_batch = TRUE, filter = TRUE) t_cf_monocyte_de_batchvisit
##
## Tumaco_cure Tumaco_failure
## 21 21
##
## 3 2 1
## 13 13 16
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_monocyte_tables_batchvisit keepers = cf_contrast,
t_cf_monocyte_de_batchvisit, # rda = glue("rda/t_monocyte_cf_table_batchvisit-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_cf_tables_batchvisit-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_cf_tables_batchvisit-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_monocyte_de_batchvisit' not found
<- extract_significant_genes(
t_cf_monocyte_sig_batchvisit
t_cf_monocyte_tables_batchvisit,excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_cf_sig_batchvisit-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_cf_sig_batchvisit-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_monocyte_tables_batchvisit, excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_cf_sig_batchvisit-v{ver}.xlsx")): object 't_cf_monocyte_tables_batchvisit' not found
dim(t_cf_monocyte_sig_batchvisit$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_sig_batchvisit' not found
dim(t_cf_monocyte_sig_batchvisit$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_sig_batchvisit' not found
Now that I am looking back over these results, I am not compeltely certain why I only did the gprofiler search for the sva data…
Up: 60 genes; 12 GO, 1 KEGG, 1 WP, 4 TF, 0 others Down: 53 genes; 26 GO, 1 KEGG, 1 Reactome, 2 TF, 0 others
<- all_gprofiler(t_cf_monocyte_sig_sva) t_cf_monocyte_sig_sva_gp
## Error in all_gprofiler(t_cf_monocyte_sig_sva): object 't_cf_monocyte_sig_sva' not found
::dotplot(t_cf_monocyte_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_monocyte_sig_sva_gp' not found
::dotplot(t_cf_monocyte_sig_sva_gp[["outcome_up"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_monocyte_sig_sva_gp' not found
::dotplot(t_cf_monocyte_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_monocyte_sig_sva_gp' not found
<- all_gprofiler(t_cf_monocyte_sig_batchvisit) t_cf_monocyte_sig_batch_gp
## Error in all_gprofiler(t_cf_monocyte_sig_batchvisit): object 't_cf_monocyte_sig_batchvisit' not found
::dotplot(t_cf_monocyte_sig_batch_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_monocyte_sig_batch_gp' not found
::dotplot(t_cf_monocyte_sig_batch_gp[["outcome_up"]][["HP_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_monocyte_sig_batch_gp' not found
Now focus in on the monocyte samples on a per-visit basis.
<- all_pairwise(tv1_monocytes, model_batch = "svaseq", filter = TRUE) t_cf_monocyte_v1_de_sva
##
## Tumaco_cure Tumaco_failure
## 8 8
## Removing 0 low-count genes (10479 remaining).
## Setting 187 low elements to zero.
## transform_counts: Found 187 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_monocyte_v1_tables_sva keepers = cf_contrast,
t_cf_monocyte_v1_de_sva, # rda = glue("rda/t_monocyte_v1_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v1_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_v1_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_monocyte_v1_de_sva' not found
<- extract_significant_genes(
t_cf_monocyte_v1_sig_sva
t_cf_monocyte_v1_tables_sva,excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v1_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_v1_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_monocyte_v1_tables_sva, excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v1_cf_sig_sva-v{ver}.xlsx")): object 't_cf_monocyte_v1_tables_sva' not found
dim(t_cf_monocyte_v1_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_v1_sig_sva' not found
dim(t_cf_monocyte_v1_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_v1_sig_sva' not found
<- all_pairwise(tv2_monocytes, model_batch = "svaseq", filter = TRUE) t_cf_monocyte_v2_de_sva
##
## Tumaco_cure Tumaco_failure
## 7 6
## Removing 0 low-count genes (10520 remaining).
## Setting 115 low elements to zero.
## transform_counts: Found 115 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_monocyte_v2_tables_sva keepers = cf_contrast,
t_cf_monocyte_v2_de_sva, # rda = glue("rda/t_monocyte_v2_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v2_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_v2_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_monocyte_v2_de_sva' not found
<- extract_significant_genes(
t_cf_monocyte_v2_sig_sva
t_cf_monocyte_v2_tables_sva,excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v2_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_v2_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_monocyte_v2_tables_sva, excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v2_cf_sig_sva-v{ver}.xlsx")): object 't_cf_monocyte_v2_tables_sva' not found
dim(t_cf_monocyte_v2_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_v2_sig_sva' not found
dim(t_cf_monocyte_v2_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_v2_sig_sva' not found
<- all_pairwise(tv3_monocytes, model_batch = "svaseq", filter = TRUE) t_cf_monocyte_v3_de_sva
##
## Tumaco_cure Tumaco_failure
## 6 7
## Removing 0 low-count genes (10374 remaining).
## Setting 55 low elements to zero.
## transform_counts: Found 55 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_monocyte_v3_tables_sva keepers = cf_contrast,
t_cf_monocyte_v3_de_sva, # rda = glue("rda/t_monocyte_v3_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v3_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_v3_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_monocyte_v3_de_sva' not found
<- extract_significant_genes(
t_cf_monocyte_v3_sig_sva
t_cf_monocyte_v3_tables_sva,excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v3_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_v3_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_monocyte_v3_tables_sva, excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_v3_cf_sig_sva-v{ver}.xlsx")): object 't_cf_monocyte_v3_tables_sva' not found
dim(t_cf_monocyte_v3_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_v3_sig_sva' not found
dim(t_cf_monocyte_v3_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_v3_sig_sva' not found
<- calculate_aucc(t_cf_monocyte_tables_sva[["data"]][[1]],
sva_aucc tbl2 = t_cf_monocyte_tables_batchvisit[["data"]][[1]],
py = "deseq_adjp", ly = "deseq_logfc")
## Error in nrow(tbl): object 't_cf_monocyte_tables_sva' not found
sva_aucc
## Error in eval(expr, envir, enclos): object 'sva_aucc' not found
<- rownames(t_cf_monocyte_tables_sva[["data"]][[1]]) %in%
shared_ids rownames(t_cf_monocyte_tables_batchvisit[["data"]][[1]])
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function '%in%': error in evaluating the argument 'x' in selecting a method for function 'rownames': object 't_cf_monocyte_tables_sva' not found
<- t_cf_monocyte_tables_sva[["data"]][[1]][shared_ids, ] first
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_tables_sva' not found
<- t_cf_monocyte_tables_batchvisit[["data"]][[1]][rownames(first), ] second
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_tables_batchvisit' not found
cor.test(first[["deseq_logfc"]], second[["deseq_logfc"]])
## Error in first[["deseq_logfc"]]: object of type 'closure' is not subsettable
V1: Up: 14 genes; No categories V1: Down: 52 genes; 20 GO, 5 TF
<- all_gprofiler(t_cf_monocyte_v1_sig_sva) t_cf_monocyte_v1_sig_sva_gp
## Error in all_gprofiler(t_cf_monocyte_v1_sig_sva): object 't_cf_monocyte_v1_sig_sva' not found
::dotplot(t_cf_monocyte_v1_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_monocyte_v1_sig_sva_gp' not found
V2: Up: 1 gene V2: Down: 0 genes.
V3: Up: 4 genes. V3: Down: 0 genes.
Switch context to the Neutrophils, once again repeat the analysis using SVA and visit as a batch factor.
<- all_pairwise(t_neutrophils, model_batch = "svaseq", filter = TRUE) t_cf_neutrophil_de_sva
##
## Tumaco_cure Tumaco_failure
## 20 21
## Removing 0 low-count genes (9099 remaining).
## Setting 750 low elements to zero.
## transform_counts: Found 750 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_neutrophil_tables_sva keepers = cf_contrast,
t_cf_neutrophil_de_sva, # rda = glue("rda/t_neutrophil_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_neutrophil_de_sva' not found
<- extract_significant_genes(
t_cf_neutrophil_sig_sva
t_cf_neutrophil_tables_sva,excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_neutrophil_tables_sva, excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_cf_sig_sva-v{ver}.xlsx")): object 't_cf_neutrophil_tables_sva' not found
dim(t_cf_neutrophil_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_sig_sva' not found
dim(t_cf_neutrophil_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_sig_sva' not found
<- all_pairwise(t_neutrophils, model_batch = TRUE, filter = TRUE) t_cf_neutrophil_de_batchvisit
##
## Tumaco_cure Tumaco_failure
## 20 21
##
## 3 2 1
## 12 13 16
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_neutrophil_tables_batchvisit keepers = cf_contrast,
t_cf_neutrophil_de_batchvisit, # rda = glue("rda/t_neutrophil_cf_table_batchvisit-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_cf_tables_batchvisit-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_cf_tables_batchvisit-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_neutrophil_de_batchvisit' not found
<- extract_significant_genes(
t_cf_neutrophil_sig_batchvisit
t_cf_neutrophil_tables_batchvisit,excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_cf_sig_batchvisit-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_cf_sig_batchvisit-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_neutrophil_tables_batchvisit, : object 't_cf_neutrophil_tables_batchvisit' not found
dim(t_cf_neutrophil_sig_batchvisit$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_sig_batchvisit' not found
dim(t_cf_neutrophil_sig_batchvisit$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_sig_batchvisit' not found
Up: 84 genes; 5 GO, 2 Reactome, 3 TF, no others. Down: 29 genes: 12 GO, 1 Reactome, 1 TF, 1 miRNA, 11 HP, 0 others
<- all_gprofiler(t_cf_neutrophil_sig_sva) t_cf_neutrophil_sig_sva_gp
## Error in all_gprofiler(t_cf_neutrophil_sig_sva): object 't_cf_neutrophil_sig_sva' not found
::dotplot(t_cf_neutrophil_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_neutrophil_sig_sva_gp' not found
::dotplot(t_cf_neutrophil_sig_sva_gp[["outcome_up"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_neutrophil_sig_sva_gp' not found
::dotplot(t_cf_neutrophil_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_neutrophil_sig_sva_gp' not found
::dotplot(t_cf_neutrophil_sig_sva_gp[["outcome_down"]][["HP_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_neutrophil_sig_sva_gp' not found
When I did this with the monocytes, I split it up into multiple blocks for each visit. This time I am just going to run them all together.
<- paste0("v", pData(t_neutrophils)[["visitnumber"]],
visitcf_factor pData(t_neutrophils)[["finaloutcome"]])
<- set_expt_conditions(t_neutrophils, fact=visitcf_factor) t_neutrophil_visitcf
## The numbers of samples by condition are:
##
## v1cure v1failure v2cure v2failure v3cure v3failure
## 8 8 7 6 5 7
<- all_pairwise(t_neutrophil_visitcf, model_batch = "svaseq",
t_cf_neutrophil_visits_de_sva filter = TRUE)
##
## v1cure v1failure v2cure v2failure v3cure v3failure
## 8 8 7 6 5 7
## Removing 0 low-count genes (9099 remaining).
## Setting 686 low elements to zero.
## transform_counts: Found 686 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_neutrophil_visits_tables_sva keepers = visitcf_contrasts,
t_cf_neutrophil_visits_de_sva, # rda = glue("rda/t_neutrophil_visitcf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_visitcf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_visitcf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_neutrophil_visits_de_sva' not found
<- extract_significant_genes(
t_cf_neutrophil_visits_sig_sva
t_cf_neutrophil_visits_tables_sva,excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_visitcf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_visitcf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_neutrophil_visits_tables_sva, : object 't_cf_neutrophil_visits_tables_sva' not found
dim(t_cf_neutrophil_visits_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_visits_sig_sva' not found
dim(t_cf_neutrophil_visits_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_visits_sig_sva' not found
<- all_pairwise(tv1_neutrophils, model_batch = "svaseq", filter = TRUE) t_cf_neutrophil_v1_de_sva
##
## Tumaco_cure Tumaco_failure
## 8 8
## Removing 0 low-count genes (8715 remaining).
## Setting 145 low elements to zero.
## transform_counts: Found 145 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_neutrophil_v1_tables_sva keepers = cf_contrast,
t_cf_neutrophil_v1_de_sva, # rda = glue("rda/t_neutrophil_v1_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v1_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_v1_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_neutrophil_v1_de_sva' not found
<- extract_significant_genes(
t_cf_neutrophil_v1_sig_sva
t_cf_neutrophil_v1_tables_sva,excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v1_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_v1_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_neutrophil_v1_tables_sva, excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v1_cf_sig_sva-v{ver}.xlsx")): object 't_cf_neutrophil_v1_tables_sva' not found
dim(t_cf_neutrophil_v1_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_v1_sig_sva' not found
dim(t_cf_neutrophil_v1_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_v1_sig_sva' not found
<- all_pairwise(tv2_neutrophils, model_batch = "svaseq", filter = TRUE) t_cf_neutrophil_v2_de_sva
##
## Tumaco_cure Tumaco_failure
## 7 6
## Removing 0 low-count genes (8450 remaining).
## Setting 78 low elements to zero.
## transform_counts: Found 78 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_neutrophil_v2_tables_sva
t_cf_neutrophil_v2_de_sva,keepers = cf_contrast,
# rda = glue("rda/t_neutrophil_v2_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v2_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_v2_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_neutrophil_v2_de_sva' not found
<- extract_significant_genes(
t_cf_neutrophil_v2_sig_sva
t_cf_neutrophil_v2_tables_sva,excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v2_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_v2_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_neutrophil_v2_tables_sva, excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v2_cf_sig_sva-v{ver}.xlsx")): object 't_cf_neutrophil_v2_tables_sva' not found
dim(t_cf_neutrophil_v2_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_v2_sig_sva' not found
dim(t_cf_neutrophil_v2_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_v2_sig_sva' not found
<- all_pairwise(tv3_neutrophils, model_batch = "svaseq", filter = TRUE) t_cf_neutrophil_v3_de_sva
##
## Tumaco_cure Tumaco_failure
## 5 7
## Removing 0 low-count genes (8503 remaining).
## Setting 83 low elements to zero.
## transform_counts: Found 83 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_neutrophil_v3_tables_sva keepers = cf_contrast,
t_cf_neutrophil_v3_de_sva, # rda = glue("rda/t_neutrophil_v3_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v3_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_v3_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_neutrophil_v3_de_sva' not found
<- extract_significant_genes(
t_cf_neutrophil_v3_sig_sva
t_cf_neutrophil_v3_tables_sva,excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v3_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Neutrophils/t_neutrophil_v3_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_neutrophil_v3_tables_sva, excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_v3_cf_sig_sva-v{ver}.xlsx")): object 't_cf_neutrophil_v3_tables_sva' not found
dim(t_cf_neutrophil_v3_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_v3_sig_sva' not found
dim(t_cf_monocyte_v3_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_v3_sig_sva' not found
V1: Up: 5 genes V1: Down: 8 genes; 14 GO.
<- all_gprofiler(t_cf_neutrophil_v1_sig_sva) t_cf_neutrophil_v1_sig_sva_gp
## Error in all_gprofiler(t_cf_neutrophil_v1_sig_sva): object 't_cf_neutrophil_v1_sig_sva' not found
::dotplot(t_cf_neutrophil_v1_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_neutrophil_v1_sig_sva_gp' not found
Up: 5 genes; 3 GO, 10 TF. Down: 1 gene.
<- calculate_aucc(t_cf_neutrophil_tables_sva[["data"]][[1]],
sva_aucc tbl2 = t_cf_neutrophil_tables_batchvisit[["data"]][[1]],
py = "deseq_adjp", ly = "deseq_logfc")
## Error in nrow(tbl): object 't_cf_neutrophil_tables_sva' not found
sva_aucc
## Error in eval(expr, envir, enclos): object 'sva_aucc' not found
<- rownames(t_cf_neutrophil_tables_sva[["data"]][[1]]) %in%
shared_ids rownames(t_cf_neutrophil_tables_batchvisit[["data"]][[1]])
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function '%in%': error in evaluating the argument 'x' in selecting a method for function 'rownames': object 't_cf_neutrophil_tables_sva' not found
<- t_cf_neutrophil_tables_sva[["data"]][[1]][shared_ids, ] first
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_tables_sva' not found
<- t_cf_neutrophil_tables_batchvisit[["data"]][[1]][rownames(first), ] second
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_tables_batchvisit' not found
cor.test(first[["deseq_logfc"]], second[["deseq_logfc"]])
## Error in first[["deseq_logfc"]]: object of type 'closure' is not subsettable
This time, with feeling! Repeating the same set of tasks with the eosinophil samples.
<- all_pairwise(t_eosinophils, model_batch = "svaseq", filter = TRUE) t_cf_eosinophil_de_sva
##
## Tumaco_cure Tumaco_failure
## 17 9
## Removing 0 low-count genes (10530 remaining).
## Setting 325 low elements to zero.
## transform_counts: Found 325 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_eosinophil_tables_sva keepers = cf_contrast,
t_cf_eosinophil_de_sva, # rda = glue("rda/t_eosinophil_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_eosinophil_de_sva' not found
<- extract_significant_genes(
t_cf_eosinophil_sig_sva
t_cf_eosinophil_tables_sva,excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_eosinophil_tables_sva, excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_cf_sig_sva-v{ver}.xlsx")): object 't_cf_eosinophil_tables_sva' not found
dim(t_cf_eosinophil_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_sig_sva' not found
dim(t_cf_eosinophil_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_sig_sva' not found
<- all_pairwise(t_eosinophils, model_batch = TRUE, filter = TRUE) t_cf_eosinophil_de_batchvisit
##
## Tumaco_cure Tumaco_failure
## 17 9
##
## 3 2 1
## 9 9 8
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_eosinophil_tables_batchvisit keepers = cf_contrast,
t_cf_eosinophil_de_batchvisit, # rda = glue("rda/t_eosinophil_cf_table_batchvisit-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_cf_tables_batchvisit-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_cf_tables_batchvisit-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_eosinophil_de_batchvisit' not found
<- extract_significant_genes(
t_cf_eosinophil_sig_batchvisit
t_cf_eosinophil_tables_batchvisit,excel = glue("excel/t_eosinophil_cf_sig_batchvisit-v{ver}.xlsx"))
## Deleting the file excel/t_eosinophil_cf_sig_batchvisit-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_eosinophil_tables_batchvisit, : object 't_cf_eosinophil_tables_batchvisit' not found
dim(t_cf_eosinophil_sig_batchvisit$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_sig_batchvisit' not found
dim(t_cf_eosinophil_sig_batchvisit$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_sig_batchvisit' not found
<- paste0("v", pData(t_eosinophils)[["visitnumber"]],
visitcf_factor pData(t_eosinophils)[["finaloutcome"]])
<- set_expt_conditions(t_eosinophils, fact = visitcf_factor) t_eosinophil_visitcf
## The numbers of samples by condition are:
##
## v1cure v1failure v2cure v2failure v3cure v3failure
## 5 3 6 3 6 3
<- all_pairwise(t_eosinophil_visitcf, model_batch = "svaseq",
t_cf_eosinophil_visits_de_sva filter = TRUE)
##
## v1cure v1failure v2cure v2failure v3cure v3failure
## 5 3 6 3 6 3
## Removing 0 low-count genes (10530 remaining).
## Setting 374 low elements to zero.
## transform_counts: Found 374 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_eosinophil_visits_tables_sva keepers = visitcf_contrasts,
t_cf_eosinophil_visits_de_sva, # rda = glue("rda/t_eosinophil_visitcf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_visitcf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_visitcf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_eosinophil_visits_de_sva' not found
<- extract_significant_genes(
t_cf_eosinophil_visits_sig_sva
t_cf_eosinophil_visits_tables_sva,excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_visitcf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_visitcf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_eosinophil_visits_tables_sva, : object 't_cf_eosinophil_visits_tables_sva' not found
dim(t_cf_eosinophil_visits_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_visits_sig_sva' not found
dim(t_cf_eosinophil_visits_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_visits_sig_sva' not found
<- color_choices[["clinic_cf"]][["Tumaco_failure"]]
num_color <- color_choices[["clinic_cf"]][["Tumaco_cure"]]
den_color <- c("FI44L", "IFI27", "PRR5", "PRR5-ARHGAP8", "RHCE",
wanted_genes "FBXO39", "RSAD2", "SMTNL1", "USP18", "AFAP1")
<- t_cf_monocyte_tables_sva[["data"]][["outcome"]] cf_monocyte_table
## Error in eval(expr, envir, enclos): object 't_cf_monocyte_tables_sva' not found
<- plot_volcano_condition_de(
cf_monocyte_volcano "outcome", label = wanted_genes,
cf_monocyte_table, fc_col = "deseq_logfc", p_col = "deseq_adjp", line_position = NULL,
color_high = num_color, color_low = den_color, label_size = 6)
## Error in is.data.frame(x): object 'cf_monocyte_table' not found
pp(file = glue("images/cf_monocyte_volcano_labeled-v{ver}.svg"))
$plot cf_monocyte_volcano
## Error in eval(expr, envir, enclos): object 'cf_monocyte_volcano' not found
dev.off()
## png
## 2
$plot cf_monocyte_volcano
## Error in eval(expr, envir, enclos): object 'cf_monocyte_volcano' not found
<- t_cf_eosinophil_tables_sva[["data"]][["outcome"]] cf_eosinophil_table
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_tables_sva' not found
<- plot_volcano_condition_de(
cf_eosinophil_volcano "outcome", label = wanted_genes,
cf_eosinophil_table, fc_col = "deseq_logfc", p_col = "deseq_adjp", line_position = NULL,
color_high = num_color, color_low = den_color, label_size = 6)
## Error in is.data.frame(x): object 'cf_eosinophil_table' not found
pp(file = glue("images/cf_eosinophil_volcano_labeled-v{ver}.svg"))
$plot cf_eosinophil_volcano
## Error in eval(expr, envir, enclos): object 'cf_eosinophil_volcano' not found
dev.off()
## png
## 2
$plot cf_eosinophil_volcano
## Error in eval(expr, envir, enclos): object 'cf_eosinophil_volcano' not found
<- t_cf_neutrophil_tables_sva[["data"]][["outcome"]] cf_neutrophil_table
## Error in eval(expr, envir, enclos): object 't_cf_neutrophil_tables_sva' not found
<- plot_volcano_condition_de(
cf_neutrophil_volcano "outcome", label = wanted_genes,
cf_neutrophil_table, fc_col = "deseq_logfc", p_col = "deseq_adjp", line_position = NULL,
color_high = num_color, color_low = den_color, label_size = 6)
## Error in is.data.frame(x): object 'cf_neutrophil_table' not found
pp(file = glue("images/cf_neutrophil_volcano_labeled-v{ver}.svg"))
$plot cf_neutrophil_volcano
## Error in eval(expr, envir, enclos): object 'cf_neutrophil_volcano' not found
dev.off()
## png
## 2
$plot cf_neutrophil_volcano
## Error in eval(expr, envir, enclos): object 'cf_neutrophil_volcano' not found
Up: 116 genes; 123 GO, 2 KEGG, 7 Reactome, 5 WP, 69 TF, 1 miRNA, 0 others Down: 74 genes; 5 GO, 1 Reactome, 4 TF, 0 others
<- all_gprofiler(t_cf_eosinophil_sig_sva) t_cf_eosinophil_sig_sva_gp
## Error in all_gprofiler(t_cf_eosinophil_sig_sva): object 't_cf_eosinophil_sig_sva' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_up"]][["REAC_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_up"]][["WP_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_up"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_down"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
<- all_pairwise(tv1_eosinophils, model_batch = "svaseq", filter = TRUE) t_cf_eosinophil_v1_de_sva
##
## Tumaco_cure Tumaco_failure
## 5 3
## Removing 0 low-count genes (9977 remaining).
## Setting 57 low elements to zero.
## transform_counts: Found 57 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_eosinophil_v1_tables_sva keepers = cf_contrast,
t_cf_eosinophil_v1_de_sva, # rda = glue("rda/t_eosinophil_v1_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v1_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_v1_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_eosinophil_v1_de_sva' not found
<- extract_significant_genes(
t_cf_eosinophil_v1_sig_sva
t_cf_eosinophil_v1_tables_sva,excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v1_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_v1_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_eosinophil_v1_tables_sva, excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v1_cf_sig_sva-v{ver}.xlsx")): object 't_cf_eosinophil_v1_tables_sva' not found
dim(t_cf_eosinophil_v1_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_v1_sig_sva' not found
dim(t_cf_eosinophil_v1_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_v1_sig_sva' not found
<- all_pairwise(tv2_eosinophils, model_batch = "svaseq", filter = TRUE) t_cf_eosinophil_v2_de_sva
##
## Tumaco_cure Tumaco_failure
## 6 3
## Removing 0 low-count genes (10115 remaining).
## Setting 90 low elements to zero.
## transform_counts: Found 90 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_eosinophil_v2_tables_sva keepers = cf_contrast,
t_cf_eosinophil_v2_de_sva, # rda = glue("rda/t_eosinophil_v2_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v2_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_v2_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_eosinophil_v2_de_sva' not found
<- extract_significant_genes(
t_cf_eosinophil_v2_sig_sva
t_cf_eosinophil_v2_tables_sva,excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v2_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_v2_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_eosinophil_v2_tables_sva, excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v2_cf_sig_sva-v{ver}.xlsx")): object 't_cf_eosinophil_v2_tables_sva' not found
dim(t_cf_eosinophil_v2_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_v2_sig_sva' not found
dim(t_cf_eosinophil_v2_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_v2_sig_sva' not found
<- all_pairwise(tv3_eosinophils, model_batch = "svaseq", filter = TRUE) t_cf_eosinophil_v3_de_sva
##
## Tumaco_cure Tumaco_failure
## 6 3
## Removing 0 low-count genes (10078 remaining).
## Setting 48 low elements to zero.
## transform_counts: Found 48 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_cf_eosinophil_v3_tables_sva keepers = cf_contrast,
t_cf_eosinophil_v3_de_sva, # rda = glue("rda/t_eosinophil_v3_cf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v3_cf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_v3_cf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_cf_eosinophil_v3_de_sva' not found
<- extract_significant_genes(
t_cf_eosinophil_v3_sig_sva
t_cf_eosinophil_v3_tables_sva,excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v3_cf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Eosinophils/t_eosinophil_v3_cf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_cf_eosinophil_v3_tables_sva, excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_v3_cf_sig_sva-v{ver}.xlsx")): object 't_cf_eosinophil_v3_tables_sva' not found
dim(t_cf_eosinophil_v3_sig_sva$deseq$ups[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_v3_sig_sva' not found
dim(t_cf_eosinophil_v3_sig_sva$deseq$downs[[1]])
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_v3_sig_sva' not found
Up: 13 genes, no hits. Down: 19 genes; 11 GO, 1 Reactome, 1 TF
<- all_gprofiler(t_cf_eosinophil_v1_sig_sva) t_cf_eosinophil_v1_sig_sva_gp
## Error in all_gprofiler(t_cf_eosinophil_v1_sig_sva): object 't_cf_eosinophil_v1_sig_sva' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_down"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_down"]][["TF_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
Up: 9 genes; 23 GO, 2 KEGG, 2 Reactome, 4 WP Down: 4 genes; no hits
<- all_gprofiler(t_cf_eosinophil_v2_sig_sva) t_cf_eosinophil_v2_sig_sva_gp
## Error in all_gprofiler(t_cf_eosinophil_v2_sig_sva): object 't_cf_eosinophil_v2_sig_sva' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_up"]][["WP_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
Up: 68 genes; 95 GO, 2 KEGG, 12 Reactome, 3 WP, 63 TF, 1 miRNA Down: 29 genes; 3 GO, 1 WP, 1 TF, 3 miRNA
<- all_gprofiler(t_cf_eosinophil_v3_sig_sva) t_cf_eosinophil_v3_sig_sva_gp
## Error in all_gprofiler(t_cf_eosinophil_v3_sig_sva): object 't_cf_eosinophil_v3_sig_sva' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_up"]][["GO_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
::dotplot(t_cf_eosinophil_sig_sva_gp[["outcome_up"]][["WP_enrich"]]) enrichplot
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'dotplot': object 't_cf_eosinophil_sig_sva_gp' not found
<- calculate_aucc(t_cf_eosinophil_tables_sva[["data"]][[1]],
sva_aucc tbl2 = t_cf_eosinophil_tables_batchvisit[["data"]][[1]],
py = "deseq_adjp", ly = "deseq_logfc")
## Error in nrow(tbl): object 't_cf_eosinophil_tables_sva' not found
sva_aucc
## Error in eval(expr, envir, enclos): object 'sva_aucc' not found
<- rownames(t_cf_eosinophil_tables_sva[["data"]][[1]]) %in%
shared_ids rownames(t_cf_eosinophil_tables_batchvisit[["data"]][[1]])
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function '%in%': error in evaluating the argument 'x' in selecting a method for function 'rownames': object 't_cf_eosinophil_tables_sva' not found
<- t_cf_eosinophil_tables_sva[["data"]][[1]][shared_ids, ] first
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_tables_sva' not found
<- t_cf_eosinophil_tables_batchvisit[["data"]][[1]][rownames(first), ] second
## Error in eval(expr, envir, enclos): object 't_cf_eosinophil_tables_batchvisit' not found
cor.test(first[["deseq_logfc"]], second[["deseq_logfc"]])
## Error in first[["deseq_logfc"]]: object of type 'closure' is not subsettable
<- calculate_aucc(t_cf_monocyte_tables_sva[["data"]][["outcome"]],
t_mono_neut_sva_aucc tbl2 = t_cf_neutrophil_tables_sva[["data"]][["outcome"]],
py = "deseq_adjp", ly = "deseq_logfc")
## Error in nrow(tbl): object 't_cf_monocyte_tables_sva' not found
t_mono_neut_sva_aucc
## Error in eval(expr, envir, enclos): object 't_mono_neut_sva_aucc' not found
<- calculate_aucc(t_cf_monocyte_tables_sva[["data"]][["outcome"]],
t_mono_eo_sva_aucc tbl2 = t_cf_eosinophil_tables_sva[["data"]][["outcome"]],
py = "deseq_adjp", ly = "deseq_logfc")
## Error in nrow(tbl): object 't_cf_monocyte_tables_sva' not found
t_mono_eo_sva_aucc
## Error in eval(expr, envir, enclos): object 't_mono_eo_sva_aucc' not found
<- calculate_aucc(t_cf_neutrophil_tables_sva[["data"]][["outcome"]],
t_neut_eo_sva_aucc tbl2 = t_cf_eosinophil_tables_sva[["data"]][["outcome"]],
py = "deseq_adjp", ly = "deseq_logfc")
## Error in nrow(tbl): object 't_cf_neutrophil_tables_sva' not found
t_neut_eo_sva_aucc
## Error in eval(expr, envir, enclos): object 't_neut_eo_sva_aucc' not found
For these contrasts, we want to see fail_v1 vs. cure_v1, fail_v2 vs. cure_v2 etc. As a result, we will need to juggle the data slightly and add another set of contrasts.
<- all_pairwise(t_visitcf, model_batch = "svaseq", filter = TRUE) t_visit_cf_all_de_sva
##
## v1cure v1failure v2cure v2failure v3cure v3failure
## 30 24 20 15 17 17
## Removing 0 low-count genes (14149 remaining).
## Setting 17117 low elements to zero.
## transform_counts: Found 17117 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_visit_cf_all_tables_sva keepers = visitcf_contrasts,
t_visit_cf_all_de_sva, # rda = glue("rda/t_all_visitcf_table_sva-v{ver}.rda"),
excel = glue("analyses/4_tumaco/DE_Cure_vs_Fail/t_all_visitcf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/t_all_visitcf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_visit_cf_all_de_sva' not found
<- extract_significant_genes(
t_visit_cf_all_sig_sva
t_visit_cf_all_tables_sva,excel = glue("analyses/4_tumaco/DE_Cure_vs_Fail/t_all_visitcf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/t_all_visitcf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_visit_cf_all_tables_sva, excel = glue("analyses/4_tumaco/DE_Cure_vs_Fail/t_all_visitcf_sig_sva-v{ver}.xlsx")): object 't_visit_cf_all_tables_sva' not found
<- all_gprofiler(t_visit_cf_all_sig_sva) t_visit_cf_all_gp
## Error in all_gprofiler(t_visit_cf_all_sig_sva): object 't_visit_cf_all_sig_sva' not found
<- paste0("v", pData(t_monocytes)[["visitnumber"]], "_",
visitcf_factor pData(t_monocytes)[["finaloutcome"]])
<- set_expt_conditions(t_monocytes, fact = visitcf_factor) t_monocytes_visitcf
## The numbers of samples by condition are:
##
## v1_cure v1_failure v2_cure v2_failure v3_cure v3_failure
## 8 8 7 6 6 7
<- all_pairwise(t_monocytes_visitcf, model_batch = "svaseq",
t_visit_cf_monocyte_de_sva filter = TRUE)
##
## v1_cure v1_failure v2_cure v2_failure v3_cure v3_failure
## 8 8 7 6 6 7
## Removing 0 low-count genes (10859 remaining).
## Setting 688 low elements to zero.
## transform_counts: Found 688 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_visit_cf_monocyte_tables_sva keepers = visitcf_contrasts,
t_visit_cf_monocyte_de_sva, # rda = glue("rda/t_monocyte_visitcf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_visitcf_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_visitcf_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_visit_cf_monocyte_de_sva' not found
<- extract_significant_genes(
t_visit_cf_monocyte_sig_sva
t_visit_cf_monocyte_tables_sva,excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_visitcf_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Cure_vs_Fail/Monocytes/t_monocyte_visitcf_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_visit_cf_monocyte_tables_sva, excel = glue("{xlsx_prefix}/Monocytes/t_monocyte_visitcf_sig_sva-v{ver}.xlsx")): object 't_visit_cf_monocyte_tables_sva' not found
<- t_visit_cf_monocyte_tables_sva[["plots"]][["v1cf"]][["deseq_ma_plots"]][["plot"]] t_v1fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_visit_cf_monocyte_tables_sva' not found
<- pp(file = "images/monocyte_cf_de_v1_maplot.png")
dev t_v1fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_v1fc_deseq_ma' not found
<- dev.off()
closed t_v1fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_v1fc_deseq_ma' not found
<- t_visit_cf_monocyte_tables_sva[["plots"]][["v2cf"]][["deseq_ma_plots"]][["plot"]] t_v2fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_visit_cf_monocyte_tables_sva' not found
<- pp(file = "images/monocyte_cf_de_v2_maplot.png")
dev t_v2fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_v2fc_deseq_ma' not found
<- dev.off()
closed t_v2fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_v2fc_deseq_ma' not found
<- t_visit_cf_monocyte_tables_sva[["plots"]][["v3cf"]][["deseq_ma_plots"]][["plot"]] t_v3fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_visit_cf_monocyte_tables_sva' not found
<- pp(file = "images/monocyte_cf_de_v3_maplot.png")
dev t_v3fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_v3fc_deseq_ma' not found
<- dev.off()
closed t_v3fc_deseq_ma
## Error in eval(expr, envir, enclos): object 't_v3fc_deseq_ma' not found
One query from Alejandro is to look at the genes shared up/down across visits. I am not entirely certain we have enough samples for this to work, but let us find out.
I am thinking this is a good place to use the AUCC curves I learned about thanks to Julie Cridland.
Note that the following is all monocyte samples, this should therefore potentially be moved up and a version of this with only the Tumaco samples put here?
<- t_visit_cf_monocyte_tables_sva[["data"]][["v1cf"]] v1cf
## Error in eval(expr, envir, enclos): object 't_visit_cf_monocyte_tables_sva' not found
<- t_visit_cf_monocyte_tables_sva[["data"]][["v2cf"]] v2cf
## Error in eval(expr, envir, enclos): object 't_visit_cf_monocyte_tables_sva' not found
<- t_visit_cf_monocyte_tables_sva[["data"]][["v3cf"]] v3cf
## Error in eval(expr, envir, enclos): object 't_visit_cf_monocyte_tables_sva' not found
<- c(
v1_sig rownames(t_visit_cf_monocyte_sig_sva[["deseq"]][["ups"]][["v1cf"]]),
rownames(t_visit_cf_monocyte_sig_sva[["deseq"]][["downs"]][["v1cf"]]))
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 't_visit_cf_monocyte_sig_sva' not found
length(v1_sig)
## Error in eval(expr, envir, enclos): object 'v1_sig' not found
<- c(
v2_sig rownames(t_visit_cf_monocyte_sig_sva[["deseq"]][["ups"]][["v2cf"]]),
rownames(t_visit_cf_monocyte_sig_sva[["deseq"]][["downs"]][["v2cf"]]))
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 't_visit_cf_monocyte_sig_sva' not found
length(v2_sig)
## Error in eval(expr, envir, enclos): object 'v2_sig' not found
<- c(
v3_sig rownames(t_visit_cf_monocyte_sig_sva[["deseq"]][["ups"]][["v2cf"]]),
rownames(t_visit_cf_monocyte_sig_sva[["deseq"]][["downs"]][["v2cf"]]))
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 't_visit_cf_monocyte_sig_sva' not found
length(v3_sig)
## Error in eval(expr, envir, enclos): object 'v3_sig' not found
<- calculate_aucc(v1cf, tbl2 = v2cf,
t_monocyte_visit_aucc_v2v1 py = "deseq_adjp", ly = "deseq_logfc")
## Error in nrow(tbl): object 'v1cf' not found
<- pp(file = "images/monocyte_visit_v2v1_aucc.png")
dev "plot"]] t_monocyte_visit_aucc_v2v1[[
## Error in eval(expr, envir, enclos): object 't_monocyte_visit_aucc_v2v1' not found
<- dev.off()
closed "plot"]] t_monocyte_visit_aucc_v2v1[[
## Error in eval(expr, envir, enclos): object 't_monocyte_visit_aucc_v2v1' not found
<- calculate_aucc(v1cf, tbl2 = v3cf,
t_monocyte_visit_aucc_v3v1 py = "deseq_adjp", ly = "deseq_logfc")
## Error in nrow(tbl): object 'v1cf' not found
<- pp(file = "images/monocyte_visit_v3v1_aucc.png")
dev "plot"]] t_monocyte_visit_aucc_v3v1[[
## Error in eval(expr, envir, enclos): object 't_monocyte_visit_aucc_v3v1' not found
<- dev.off()
closed "plot"]] t_monocyte_visit_aucc_v3v1[[
## Error in eval(expr, envir, enclos): object 't_monocyte_visit_aucc_v3v1' not found
<- paste0("v", pData(t_neutrophils)[["visitnumber"]], "_",
visitcf_factor pData(t_neutrophils)[["finaloutcome"]])
<- set_expt_conditions(t_neutrophils, fact = visitcf_factor) t_neutrophil_visitcf
## The numbers of samples by condition are:
##
## v1_cure v1_failure v2_cure v2_failure v3_cure v3_failure
## 8 8 7 6 5 7
<- all_pairwise(t_neutrophil_visitcf, model_batch = "svaseq",
t_visit_cf_neutrophil_de_sva filter = TRUE)
##
## v1_cure v1_failure v2_cure v2_failure v3_cure v3_failure
## 8 8 7 6 5 7
## Removing 0 low-count genes (9099 remaining).
## Setting 686 low elements to zero.
## transform_counts: Found 686 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_visit_cf_neutrophil_tables_sva keepers = visitcf_contrasts,
t_visit_cf_neutrophil_de_sva, # rda = glue("rda/t_neutrophil_visitcf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_visitcf_tables_sva-v{ver}.xlsx"))
## Error in get_expt_colors(apr[["input"]]): object 't_visit_cf_neutrophil_de_sva' not found
<- extract_significant_genes(
t_visit_cf_neutrophil_sig_sva
t_visit_cf_neutrophil_tables_sva,excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_visitcf_sig_sva-v{ver}.xlsx"))
## Error in extract_significant_genes(t_visit_cf_neutrophil_tables_sva, excel = glue("{xlsx_prefix}/Neutrophils/t_neutrophil_visitcf_sig_sva-v{ver}.xlsx")): object 't_visit_cf_neutrophil_tables_sva' not found
<- paste0("v", pData(t_eosinophils)[["visitnumber"]], "_",
visitcf_factor pData(t_eosinophils)[["finaloutcome"]])
<- set_expt_conditions(t_eosinophils, fact = visitcf_factor) t_eosinophil_visitcf
## The numbers of samples by condition are:
##
## v1_cure v1_failure v2_cure v2_failure v3_cure v3_failure
## 5 3 6 3 6 3
<- all_pairwise(t_eosinophil_visitcf, model_batch = "svaseq",
t_visit_cf_eosinophil_de_sva filter = TRUE)
##
## v1_cure v1_failure v2_cure v2_failure v3_cure v3_failure
## 5 3 6 3 6 3
## Removing 0 low-count genes (10530 remaining).
## Setting 374 low elements to zero.
## transform_counts: Found 374 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_visit_cf_eosinophil_tables_sva keepers = visitcf_contrasts,
t_visit_cf_eosinophil_de_sva, # rda = glue("rda/t_eosinophil_visitcf_table_sva-v{ver}.rda"),
excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_visitcf_tables_sva-v{ver}.xlsx"))
## Error in get_expt_colors(apr[["input"]]): object 't_visit_cf_eosinophil_de_sva' not found
<- extract_significant_genes(
t_visit_cf_eosinophil_sig_sva
t_visit_cf_eosinophil_tables_sva,excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_visitcf_sig_sva-v{ver}.xlsx"))
## Error in extract_significant_genes(t_visit_cf_eosinophil_tables_sva, excel = glue("{xlsx_prefix}/Eosinophils/t_eosinophil_visitcf_sig_sva-v{ver}.xlsx")): object 't_visit_cf_eosinophil_tables_sva' not found
Having put some SL read mapping information in the sample sheet, Maria Adelaida added a new column using it with the putative persistence state on a per-sample basis. One question which arised from that: what differences are observable between the persistent yes vs. no samples on a per-cell-type basis among the visit 3 samples.
First things first, create the datasets.
<- subset_expt(t_clinical, subset = "persistence=='Y'|persistence=='N'") %>%
persistence_expt subset_expt(subset = 'visitnumber==3') %>%
set_expt_conditions(fact = 'persistence')
## subset_expt(): There were 123, now there are 97 samples.
## subset_expt(): There were 97, now there are 30 samples.
## The numbers of samples by condition are:
##
## N Y
## 6 24
## persistence_biopsy <- subset_expt(persistence_expt, subset = "typeofcells=='biopsy'")
<- subset_expt(persistence_expt, subset = "typeofcells=='monocytes'") persistence_monocyte
## subset_expt(): There were 30, now there are 12 samples.
<- subset_expt(persistence_expt, subset = "typeofcells=='neutrophils'") persistence_neutrophil
## subset_expt(): There were 30, now there are 10 samples.
<- subset_expt(persistence_expt, subset = "typeofcells=='eosinophils'") persistence_eosinophil
## subset_expt(): There were 30, now there are 8 samples.
See if there are any patterns which look usable.
## All
<- normalize_expt(persistence_expt, transform = "log2", convert = "cpm",
persistence_norm norm = "quant", filter = TRUE)
## Removing 8537 low-count genes (11386 remaining).
## transform_counts: Found 15 values equal to 0, adding 1 to the matrix.
plot_pca(persistence_norm)$plot
<- normalize_expt(persistence_expt, transform = "log2", convert = "cpm",
persistence_nb batch = "svaseq", filter = TRUE)
## Removing 8537 low-count genes (11386 remaining).
## Setting 1538 low elements to zero.
## transform_counts: Found 1538 values equal to 0, adding 1 to the matrix.
plot_pca(persistence_nb)$plot
## Biopsies
##persistence_biopsy_norm <- normalize_expt(persistence_biopsy, transform = "log2", convert = "cpm",
## norm = "quant", filter = TRUE)
##plot_pca(persistence_biopsy_norm)$plot
## Insufficient data
## Monocytes
<- normalize_expt(persistence_monocyte, transform = "log2", convert = "cpm",
persistence_monocyte_norm norm = "quant", filter = TRUE)
## Removing 9597 low-count genes (10326 remaining).
## transform_counts: Found 1 values equal to 0, adding 1 to the matrix.
plot_pca(persistence_monocyte_norm)$plot
<- normalize_expt(persistence_monocyte, transform = "log2", convert = "cpm",
persistence_monocyte_nb batch = "svaseq", filter = TRUE)
## Removing 9597 low-count genes (10326 remaining).
## Setting 46 low elements to zero.
## transform_counts: Found 46 values equal to 0, adding 1 to the matrix.
plot_pca(persistence_monocyte_nb)$plot
## Neutrophils
<- normalize_expt(persistence_neutrophil, transform = "log2", convert = "cpm",
persistence_neutrophil_norm norm = "quant", filter = TRUE)
## Removing 11531 low-count genes (8392 remaining).
## transform_counts: Found 2 values equal to 0, adding 1 to the matrix.
plot_pca(persistence_neutrophil_norm)$plot
<- normalize_expt(persistence_neutrophil, transform = "log2", convert = "cpm",
persistence_neutrophil_nb batch = "svaseq", filter = TRUE)
## Removing 11531 low-count genes (8392 remaining).
## Setting 46 low elements to zero.
## transform_counts: Found 46 values equal to 0, adding 1 to the matrix.
plot_pca(persistence_neutrophil_nb)$plot
## Eosinophils
<- normalize_expt(persistence_eosinophil, transform = "log2", convert = "cpm",
persistence_eosinophil_norm norm = "quant", filter = TRUE)
## Removing 9895 low-count genes (10028 remaining).
## transform_counts: Found 1 values equal to 0, adding 1 to the matrix.
plot_pca(persistence_eosinophil_norm)$plot
<- normalize_expt(persistence_eosinophil, transform = "log2", convert = "cpm",
persistence_eosinophil_nb batch = "svaseq", filter = TRUE)
## Removing 9895 low-count genes (10028 remaining).
## Setting 25 low elements to zero.
## transform_counts: Found 25 values equal to 0, adding 1 to the matrix.
plot_pca(persistence_eosinophil_nb)$plot
<- all_pairwise(persistence_expt, filter = TRUE, model_batch = "svaseq") persistence_de_sva
##
## N Y
## 6 24
## Removing 0 low-count genes (11386 remaining).
## Setting 1538 low elements to zero.
## transform_counts: Found 1538 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
persistence_table_sva
persistence_de_sva,excel = glue("analyses/4_tumaco/DE_Persistence/persistence_all_de_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Persistence/persistence_all_de_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'persistence_de_sva' not found
<- all_pairwise(persistence_monocyte, filter = TRUE, model_batch = "svaseq") persistence_monocyte_de_sva
##
## N Y
## 2 10
## Removing 0 low-count genes (10326 remaining).
## Setting 46 low elements to zero.
## transform_counts: Found 46 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
persistence_monocyte_table_sva
persistence_monocyte_de_sva,excel = glue("analyses/4_tumaco/DE_Persistence/persistence_monocyte_de_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Persistence/persistence_monocyte_de_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'persistence_monocyte_de_sva' not found
<- all_pairwise(persistence_neutrophil, filter = TRUE, model_batch = "svaseq") persistence_neutrophil_de_sva
##
## N Y
## 3 7
## Removing 0 low-count genes (8392 remaining).
## Setting 46 low elements to zero.
## transform_counts: Found 46 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
persistence_neutrophil_table_sva
persistence_neutrophil_de_sva,excel = glue("analyses/4_tumaco/DE_Persistence/persistence_neutrophil_de_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Persistence/persistence_neutrophil_de_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 'persistence_neutrophil_de_sva' not found
<- all_pairwise(persistence_eosinophil, filter = TRUE, model_batch = "svaseq") persistence_eosinophil_de_sva
##
## N Y
## 1 7
## Removing 0 low-count genes (10028 remaining).
## Setting 25 low elements to zero.
## transform_counts: Found 25 values equal to 0, adding 1 to the matrix.
## Error in checkForRemoteErrors(val): one node produced an error: c("Error in NOISeq::noiseqbio(norm, k = 0.5, norm = \"rpkm\", factor = \"condition\", : \n ERROR: To run NOISeqBIO at least two replicates per condition are needed.\n Please, run NOISeq if there are not enough replicates in your experiment.\n\n", "noiseq")
<- combine_de_tables(
persistence_eosinophil_table_sva
persistence_eosinophil_de_sva,excel = glue("analyses/4_tumaco/DE_Persistence/persistence_eosinophil_de_sva-v{ver}.xlsx"))
## Error in get_expt_colors(apr[["input"]]): object 'persistence_eosinophil_de_sva' not found
<- all_pairwise(t_visit, filter = TRUE, model_batch = "svaseq") t_visit_all_de_sva
##
## 3 2 1
## 34 35 40
## Removing 0 low-count genes (11907 remaining).
## Setting 9614 low elements to zero.
## transform_counts: Found 9614 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_visit_all_table_sva keepers = visit_contrasts,
t_visit_all_de_sva, # rda = glue("rda/t_all_visit_table_sva-v{ver}.rda"),
excel = glue("analyses/4_tumaco/DE_Visits/t_all_visit_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Visits/t_all_visit_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_visit_all_de_sva' not found
<- extract_significant_genes(
t_visit_all_sig_sva
t_visit_all_table_sva,excel = glue("analyses/4_tumaco/DE_Visits/t_all_visit_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Visits/t_all_visit_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_visit_all_table_sva, excel = glue("analyses/4_tumaco/DE_Visits/t_all_visit_sig_sva-v{ver}.xlsx")): object 't_visit_all_table_sva' not found
<- set_expt_conditions(t_monocytes, fact = "visitnumber") t_visit_monocytes
## The numbers of samples by condition are:
##
## 3 2 1
## 13 13 16
<- all_pairwise(t_visit_monocytes, filter = TRUE, model_batch = "svaseq") t_visit_monocyte_de_sva
##
## 3 2 1
## 13 13 16
## Removing 0 low-count genes (10859 remaining).
## Setting 648 low elements to zero.
## transform_counts: Found 648 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_visit_monocyte_table_sva keepers = visit_contrasts,
t_visit_monocyte_de_sva, # rda = glue("rda/t_monocyte_visit_table_sva-v{ver}.rda"),
excel = glue("analyses/4_tumaco/DE_Visits/Monocytes/t_monocyte_visit_tables_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Visits/Monocytes/t_monocyte_visit_tables_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_visit_monocyte_de_sva' not found
<- extract_significant_genes(
t_visit_monocyte_sig_sva
t_visit_monocyte_table_sva,excel = glue("analyses/4_tumaco/DE_Visits/Monocytes/t_monocyte_visit_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Visits/Monocytes/t_monocyte_visit_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_visit_monocyte_table_sva, excel = glue("analyses/4_tumaco/DE_Visits/Monocytes/t_monocyte_visit_sig_sva-v{ver}.xlsx")): object 't_visit_monocyte_table_sva' not found
<- set_expt_conditions(t_neutrophils, fact = "visitnumber") t_visit_neutrophils
## The numbers of samples by condition are:
##
## 3 2 1
## 12 13 16
<- all_pairwise(t_visit_neutrophils, filter = TRUE, model_batch = "svaseq") t_visit_neutrophil_de_sva
##
## 3 2 1
## 12 13 16
## Removing 0 low-count genes (9099 remaining).
## Setting 589 low elements to zero.
## transform_counts: Found 589 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_visit_neutrophil_table_sva keepers = visit_contrasts,
t_visit_neutrophil_de_sva, # rda = glue("rda/t_neutrophil_visit_table_sva-v{ver}.rda"),
excel = glue("analyses/4_tumaco/DE_Visits/Neutrophils/t_neutrophil_visit_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Visits/Neutrophils/t_neutrophil_visit_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_visit_neutrophil_de_sva' not found
<- extract_significant_genes(
t_visit_neutrophil_sig_sva
t_visit_neutrophil_table_sva,excel = glue("analyses/4_tumaco/DE_Visits/Neutrophils/t_neutrophil_visit_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Visits/Neutrophils/t_neutrophil_visit_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_visit_neutrophil_table_sva, excel = glue("analyses/4_tumaco/DE_Visits/Neutrophils/t_neutrophil_visit_sig_sva-v{ver}.xlsx")): object 't_visit_neutrophil_table_sva' not found
<- set_expt_conditions(t_eosinophils, fact="visitnumber") t_visit_eosinophils
## The numbers of samples by condition are:
##
## 3 2 1
## 9 9 8
<- all_pairwise(t_visit_eosinophils, filter = TRUE, model_batch = "svaseq") t_visit_eosinophil_de
##
## 3 2 1
## 9 9 8
## Removing 0 low-count genes (10530 remaining).
## Setting 272 low elements to zero.
## transform_counts: Found 272 values equal to 0, adding 1 to the matrix.
## Error in retlst[[meth]]: attempt to select less than one element in get1index
<- combine_de_tables(
t_visit_eosinophil_table keepers = visit_contrasts,
t_visit_eosinophil_de, # rda = glue("rda/t_eosinophil_visit_table_sva-v{ver}.rda"),
excel = glue("analyses/4_tumaco/DE_Visits/Eosinophils/t_eosinophil_visit_table_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Visits/Eosinophils/t_eosinophil_visit_table_sva-v202305.xlsx before writing the tables.
## Error in get_expt_colors(apr[["input"]]): object 't_visit_eosinophil_de' not found
<- extract_significant_genes(
t_visit_eosinophil_sig
t_visit_eosinophil_table,excel = glue("analyses/4_tumaco/DE_Visits/Eosinophils/t_eosinophil_visit_sig_sva-v{ver}.xlsx"))
## Deleting the file analyses/4_tumaco/DE_Visits/Eosinophils/t_eosinophil_visit_sig_sva-v202305.xlsx before writing the tables.
## Error in extract_significant_genes(t_visit_eosinophil_table, excel = glue("analyses/4_tumaco/DE_Visits/Eosinophils/t_eosinophil_visit_sig_sva-v{ver}.xlsx")): object 't_visit_eosinophil_table' not found
Alejandro showed some ROC curves for eosinophil data showing sensitivity vs. specificity of a couple genes which were observed in v1 eosinophils vs. all-times eosinophils across cure/fail. I am curious to better understand how this was done and what utility it might have in other contexts.
To that end, I want to try something similar myself. In order to properly perform the analysis with these various tools, I need to reconfigure the data in a pretty specific format:
If I intend to use this for our tx data, I will likely need a utility function to create the properly formatted input df.
For the purposes of my playing, I will choose three genes from the eosinophil C/F table, one which is significant, one which is not, and an arbitrary.
The input genes will therefore be chosen from the data structure: t_cf_eosinophil_tables_sva:
ENSG00000198178, ENSG00000179344, ENSG00000182628
<- normalize_expt(tv1_eosinophils, convert = "rpkm", column = "cds_length") eo_rpkm
## There appear to be 5391 genes without a length.
<- all_pairwise(tmrc_external, model_batch = "svaseq", filter = "simple") test
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'tmrc_external' not found
<- combine_de_tables(test, excel = "excel/tmrc3_scott_biopsies.xlsx") test_table
## Error in get_expt_colors(apr[["input"]]): object 'test' not found
<- extract_significant_genes(test_table, excel = "excel/tmrc3_scott_biopsies_sig.xlsx") test_sig
## Error in extract_significant_genes(test_table, excel = "excel/tmrc3_scott_biopsies_sig.xlsx"): object 'test_table' not found
<- set_expt_conditions(tmrc_external, fact = "ParasiteSpecies") %>%
tmrc_external_species set_expt_colors(color_choices[["parasite"]])
## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': error in evaluating the argument 'object' in selecting a method for function 'pData': object 'tmrc_external' not found
## Skipping this because it is taking too long.
##if (!isTRUE(get0("skip_load"))) {
## pander::pander(sessionInfo())
## message(paste0("This is hpgltools commit: ", get_git_commit()))
## message(paste0("Saving to ", savefile))
## tmp <- sm(saveme(filename=savefile))
##}
<- loadme(filename = savefile) tmp