Having established that the TMRC2 macrophage data looks robust and illustrative of a couple of interesting questions, let us perform a couple of differential analyses of it.
Also note that as of 202212, we received a new set of samples which now include some which are of a completely different cell type, U937. As their ATCC page states, they are malignant cells taken from the pleural effusion of a 37 year old white male with histiocytic lymphoma and which exhibit the morphology of monocytes. Thus, this document now includes some comparisons of the cell types as well as the various macrophage donors (given that there are now more donors too).
I am moving the dataset manipulations here so that I can look at them all together before running the various DE analyses.
all_human <- sanitize_expt_metadata(hs_macrophage, columns = "drug") %>%
set_expt_conditions(fact = "drug") %>%
set_expt_batches(fact = "typeofcells")
all_human_types <- set_expt_conditions(all_human, fact = "typeofcells") %>%
set_expt_batches(fact = "drug")
type_zymo_fact <- paste0(pData(all_human_types)[["condition"]], "_",
pData(all_human_types)[["macrophagezymodeme"]])
type_zymo <- set_expt_conditions(all_human_types, fact = type_zymo_fact)
type_drug_fact <- paste0(pData(all_human_types)[["condition"]], "_",
pData(all_human_types)[["drug"]])
type_drug <- set_expt_conditions(all_human_types, fact=type_drug_fact)
extra <- "z23drugnodrug_vs_z22drugnodrug = (infsbz23 - infz23) - (infsbz22 - infz22)"
new_conditions <- paste0(pData(hs_macr)[["macrophagetreatment"]], "_",
pData(hs_macr)[["macrophagezymodeme"]])## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_macr' not foundhs_macr <- set_expt_conditions(hs_macr, fact = new_conditions)## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_macr' not foundnew_conditions <- paste0(pData(hs_u937)[["macrophagetreatment"]], "_",
pData(hs_u937)[["macrophagezymodeme"]])## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_u937' not foundu937_expt <- set_expt_conditions(hs_u937, fact=new_conditions)## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_u937' not foundtmrc2_human_keepers <- list(
"z23nosb_vs_uninf" = c("infz23", "uninfnone"),
"z22nosb_vs_uninf" = c("infz22", "uninfnone"),
"z23nosb_vs_z22nosb" = c("infz23", "infz22"),
"z23sb_vs_z22sb" = c("infsbz23", "infsbz22"),
"z23sb_vs_z23nosb" = c("infsbz23", "infz23"),
"z22sb_vs_z22nosb" = c("infsbz22", "infz22"),
"z23sb_vs_sb" = c("infz23", "uninfsbnone"),
"z22sb_vs_sb" = c("infz22", "uninfsbnone"),
"z23sb_vs_uninf" = c("infsbz23", "uninfnone"),
"z22sb_vs_uninf" = c("infsbz22", "uninfnone"),
"sb_vs_uninf" = c("uninfsbnone", "uninfnone"))
## "extra" = c("z23drugnodrug", "z22drugnodrug"))There is a series of initial questions which make some sense to me, but these do not necessarily match the set of questions which are most pressing. I am hoping to pull both of these sets of queries in one.
Before extracting these groups of queries, let us invoke the all_pairwise() function and get all of the likely contrasts along with one or more extras that might prove useful (the ‘extra’ argument).
When we have the u937 cells in the same dataset as the macrophages, that provides an interesting opportunity to see if we can observe drug-dependant effects which are shared across both cell types.
drug_de <- all_pairwise(all_human, filter = TRUE, model_batch = "svaseq")## This DE analysis will perform all pairwise comparisons among:##
## antimony none
## 34 34## This analysis will include surrogate estimates from: svaseq.## This will pre-filter the input data using normalize_expt's: TRUE argument.## Removing 0 low-count genes (12283 remaining).## Setting 3092 low elements to zero.## transform_counts: Found 3092 values equal to 0, adding 1 to the matrix.## Finished running DE analyses, collecting outputs.## Comparing analyses.drug_table <- combine_de_tables(
drug_de,
excel = glue::glue("excel/tmrc2_macrophage_drug_comparison-v{ver}.xlsx"))## Deleting the file excel/tmrc2_macrophage_drug_comparison-v202212.xlsx before writing the tables.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of none_vs_antimony according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of none_vs_antimony according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of none_vs_antimony according to the columns: logFC and adj.P.Val using the expressionset colors.There are a couple of ways one might want to directly compare the two cell types.
type_de <- all_pairwise(all_human_types, filter = TRUE, model_batch = "svaseq")## This DE analysis will perform all pairwise comparisons among:##
## Macrophages U937
## 54 14## This analysis will include surrogate estimates from: svaseq.## This will pre-filter the input data using normalize_expt's: TRUE argument.## Removing 0 low-count genes (12283 remaining).## Setting 8682 low elements to zero.## transform_counts: Found 8682 values equal to 0, adding 1 to the matrix.## Finished running DE analyses, collecting outputs.## Comparing analyses.type_table <- combine_de_tables(
type_de,
excel = glue::glue("excel/tmrc2_macrophage_type_comparison-v{ver}.xlsx"))## Deleting the file excel/tmrc2_macrophage_type_comparison-v202212.xlsx before writing the tables.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937_vs_Macrophages according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937_vs_Macrophages according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937_vs_Macrophages according to the columns: logFC and adj.P.Val using the expressionset colors.Given the above explicit comparison of all samples comprising the two cell types, now let us look at the drug treatment+zymodeme status with all samples, macrophages and U937.
type_zymo_de <- all_pairwise(type_zymo, filter = TRUE, model_batch = "svaseq")## This DE analysis will perform all pairwise comparisons among:##
## Macrophages_none Macrophages_z2.2 Macrophages_z2.3 U937_none
## 8 23 23 2
## U937_z2.2 U937_z2.3
## 6 6## This analysis will include surrogate estimates from: svaseq.## This will pre-filter the input data using normalize_expt's: TRUE argument.## Removing 0 low-count genes (12283 remaining).## Setting 9655 low elements to zero.## transform_counts: Found 9655 values equal to 0, adding 1 to the matrix.## Finished running DE analyses, collecting outputs.## Comparing analyses.
type_zymo_table <- combine_de_tables(
type_zymo_de,
excel = glue::glue("excel/tmrc2_macrophage_type_zymo_comparison-v{ver}.xlsx"))## Deleting the file excel/tmrc2_macrophage_type_zymo_comparison-v202212.xlsx before writing the tables.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of Macrophagesz22_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of Macrophagesz22_vs_Macrophagesnone according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of Macrophagesz22_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of Macrophagesz23_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of Macrophagesz23_vs_Macrophagesnone according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of Macrophagesz23_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesnone according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesnone according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesnone according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of Macrophagesz23_vs_Macrophagesz22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of Macrophagesz23_vs_Macrophagesz22 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of Macrophagesz23_vs_Macrophagesz22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesz22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesz22 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesz22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesz22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesz22 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesz22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesz22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesz22 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesz22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesz23 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesz23 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesz23 according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesz23 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesz23 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z22_vs_Macrophagesz23 according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesz23 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesz23 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_Macrophagesz23 according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z22_vs_U937none according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z22_vs_U937none according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z22_vs_U937none according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z23_vs_U937none according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_U937none according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_U937none according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937z23_vs_U937z22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_U937z22 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937z23_vs_U937z22 according to the columns: logFC and adj.P.Val using the expressionset colors.type_drug_de <- all_pairwise(type_drug, filter = TRUE, model_batch = "svaseq")## This DE analysis will perform all pairwise comparisons among:##
## Macrophages_antimony Macrophages_none U937_antimony
## 27 27 7
## U937_none
## 7## This analysis will include surrogate estimates from: svaseq.## This will pre-filter the input data using normalize_expt's: TRUE argument.## Removing 0 low-count genes (12283 remaining).## Setting 9642 low elements to zero.## transform_counts: Found 9642 values equal to 0, adding 1 to the matrix.## Finished running DE analyses, collecting outputs.## Comparing analyses.
type_drug_table <- combine_de_tables(
type_drug_de,
excel=glue::glue("excel/tmrc2_macrophage_type_drug_comparison-v{ver}.xlsx"))## Deleting the file excel/tmrc2_macrophage_type_drug_comparison-v202212.xlsx before writing the tables.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of Macrophagesnone_vs_Macrophagesantimony according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of Macrophagesnone_vs_Macrophagesantimony according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of Macrophagesnone_vs_Macrophagesantimony according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937antimony_vs_Macrophagesantimony according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937antimony_vs_Macrophagesantimony according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937antimony_vs_Macrophagesantimony according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesantimony according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesantimony according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesantimony according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937antimony_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937antimony_vs_Macrophagesnone according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937antimony_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesnone according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_Macrophagesnone according to the columns: logFC and adj.P.Val using the expressionset colors.## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of U937none_vs_U937antimony according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_U937antimony according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of U937none_vs_U937antimony according to the columns: logFC and adj.P.Val using the expressionset colors.hs_macr_de <- all_pairwise(hs_macr, model_batch = "svaseq", filter = TRUE)## This DE analysis will perform all pairwise comparisons among:## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_macr' not foundhs_macr_table <- combine_de_tables(
hs_macr_de,
keepers = tmrc2_human_keepers,
excel = glue::glue("excel/hs_macr_drug_zymo_table-v{ver}.xlsx"))## Deleting the file excel/hs_macr_drug_zymo_table-v202212.xlsx before writing the tables.## Error in combine_de_tables(hs_macr_de, keepers = tmrc2_human_keepers, : object 'hs_macr_de' not found## extra_contrasts = extra)
hs_macr_sig <- extract_significant_genes(
hs_macr_table,
excel = glue::glue("excel/hs_macr_drug_zymo_sig-v{ver}.xlsx"))## Deleting the file excel/hs_macr_drug_zymo_sig-v202212.xlsx before writing the tables.## Error in extract_significant_genes(hs_macr_table, excel = glue::glue("excel/hs_macr_drug_zymo_sig-v{ver}.xlsx")): object 'hs_macr_table' not foundu937_de <- all_pairwise(u937_expt, model_batch = "svaseq", filter = TRUE)## This DE analysis will perform all pairwise comparisons among:## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'u937_expt' not found## extra_contrasts=extra)
u937_table <- combine_de_tables(
u937_de,
keepers = tmrc2_human_keepers,
excel = glue::glue("excel/u937_drug_zymo_table-v{ver}.xlsx"))## Deleting the file excel/u937_drug_zymo_table-v202212.xlsx before writing the tables.## Error in combine_de_tables(u937_de, keepers = tmrc2_human_keepers, excel = glue::glue("excel/u937_drug_zymo_table-v{ver}.xlsx")): object 'u937_de' not foundu937_sig <- extract_significant_genes(
u937_table,
excel = glue::glue("excel/u937_drug_zymo_sig-v{ver}.xlsx"))## Deleting the file excel/u937_drug_zymo_sig-v202212.xlsx before writing the tables.## Error in extract_significant_genes(u937_table, excel = glue::glue("excel/u937_drug_zymo_sig-v{ver}.xlsx")): object 'u937_table' not foundupset_plots_hs_macr <- upsetr_sig(
hs_macr_sig, both = TRUE,
contrasts = c("z23sb_vs_z22sb", "z23nosb_vs_z22nosb"))## Error in upsetr_sig(hs_macr_sig, both = TRUE, contrasts = c("z23sb_vs_z22sb", : object 'hs_macr_sig' not foundupset_plots_hs_macr[["both"]]## Error in eval(expr, envir, enclos): object 'upset_plots_hs_macr' not foundgroups <- upset_plots_hs_macr[["both_groups"]]## Error in eval(expr, envir, enclos): object 'upset_plots_hs_macr' not foundshared_genes <- attr(groups, "elements")[groups[[2]]] %>%
gsub(pattern = "^gene:", replacement = "")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'gsub': object 'groups' not foundlength(shared_genes)## Error in eval(expr, envir, enclos): object 'shared_genes' not foundshared_gp <- simple_gprofiler(shared_genes)## Error in "character" %in% class(sig_genes): object 'shared_genes' not foundshared_gp[["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'shared_gp' not foundpp(file="images/shared_genes_bp.png")
shared_gp[["pvalue_plots"]][["BP"]]## Error in eval(expr, envir, enclos): object 'shared_gp' not founddev.off()## png
## 2shared_gp[["pvalue_plots"]][["REAC"]]## Error in eval(expr, envir, enclos): object 'shared_gp' not founddrug_genes <- attr(groups, "elements")[groups[["z23sb_vs_z22sb"]]] %>%
gsub(pattern = "^gene:", replacement = "")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'gsub': object 'groups' not founddrugonly_gp <- simple_gprofiler(drug_genes)## Error in "character" %in% class(sig_genes): object 'drug_genes' not founddrugonly_gp[["pvalue_plots"]][["BP"]]## Error in eval(expr, envir, enclos): object 'drugonly_gp' not foundI want to try something, directly include the u937 data in this…
both_sig <- hs_macr_sig## Error in eval(expr, envir, enclos): object 'hs_macr_sig' not foundnames(both_sig[["deseq"]][["ups"]]) <- paste0("macr_", names(both_sig[["deseq"]][["ups"]]))## Error in paste0("macr_", names(both_sig[["deseq"]][["ups"]])): object 'both_sig' not foundnames(both_sig[["deseq"]][["downs"]]) <- paste0("macr_", names(both_sig[["deseq"]][["downs"]]))## Error in paste0("macr_", names(both_sig[["deseq"]][["downs"]])): object 'both_sig' not foundu937_deseq <- u937_sig[["deseq"]]## Error in eval(expr, envir, enclos): object 'u937_sig' not foundnames(u937_deseq[["ups"]]) <- paste0("u937_", names(u937_deseq[["ups"]]))## Error in paste0("u937_", names(u937_deseq[["ups"]])): object 'u937_deseq' not foundnames(u937_deseq[["downs"]]) <- paste0("u937_", names(u937_deseq[["downs"]]))## Error in paste0("u937_", names(u937_deseq[["downs"]])): object 'u937_deseq' not foundboth_sig[["deseq"]][["ups"]] <- c(both_sig[["deseq"]][["ups"]], u937_deseq[["ups"]])## Error in eval(expr, envir, enclos): object 'both_sig' not foundboth_sig[["deseq"]][["downs"]] <- c(both_sig[["deseq"]][["ups"]], u937_deseq[["downs"]])## Error in eval(expr, envir, enclos): object 'both_sig' not foundsummary(both_sig[["deseq"]][["ups"]])## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'both_sig' not foundupset_plots_both <- upsetr_sig(
both_sig, both=TRUE,
contrasts=c("macr_z23sb_vs_z22sb", "macr_z23nosb_vs_z22nosb",
"u937_z23sb_vs_z22sb", "u937_z23nosb_vs_z22nosb"))## Error in upsetr_sig(both_sig, both = TRUE, contrasts = c("macr_z23sb_vs_z22sb", : object 'both_sig' not foundupset_plots_both$both## Error in eval(expr, envir, enclos): object 'upset_plots_both' not foundLooking a bit more closely at these, I think the u937 data is too sparse to effectively compare.
macr_u937_comparison <- compare_de_results(hs_macr_table, u937_table)## Testing method: limma.## Error: object 'hs_macr_table' not foundmacr_u937_comparison$lfc_heat## Error in eval(expr, envir, enclos): object 'macr_u937_comparison' not foundmacr_u937_venns <- compare_significant_contrasts(hs_macr_sig, second_sig_tables = u937_sig,
contrasts = "z23sb_vs_z23nosb")## Error in compare_significant_contrasts(hs_macr_sig, second_sig_tables = u937_sig, : object 'hs_macr_sig' not foundmacr_u937_venns$up_plot## Error in eval(expr, envir, enclos): object 'macr_u937_venns' not foundmacr_u937_venns$down_plot## Error in eval(expr, envir, enclos): object 'macr_u937_venns' not foundmacr_u937_venns_v2 <- compare_significant_contrasts(hs_macr_sig, second_sig_tables = u937_sig,
contrasts = "z22sb_vs_z22nosb")## Error in compare_significant_contrasts(hs_macr_sig, second_sig_tables = u937_sig, : object 'hs_macr_sig' not foundmacr_u937_venns_v2$up_plot## Error in eval(expr, envir, enclos): object 'macr_u937_venns_v2' not foundmacr_u937_venns_v2$down_plot## Error in eval(expr, envir, enclos): object 'macr_u937_venns_v2' not foundmacr_u937_venns_v3 <- compare_significant_contrasts(hs_macr_sig, second_sig_tables = u937_sig,
contrasts = "sb_vs_uninf")## Error in compare_significant_contrasts(hs_macr_sig, second_sig_tables = u937_sig, : object 'hs_macr_sig' not foundmacr_u937_venns_v3$up_plot## Error in eval(expr, envir, enclos): object 'macr_u937_venns_v3' not foundmacr_u937_venns_v3$down_plot## Error in eval(expr, envir, enclos): object 'macr_u937_venns_v3' not foundcomparison_df <- merge(hs_macr_table[["data"]][["z23sb_vs_z22sb"]],
u937_table[["data"]][["z23sb_vs_z22sb"]],
by = "row.names")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'hs_macr_table' not foundmacru937_z23z22_plot <- plot_linear_scatter(comparison_df[, c("deseq_logfc.x", "deseq_logfc.y")])## Error in data.frame(df[, c(1, 2)]): object 'comparison_df' not foundmacru937_z23z22_plot$scatter## Error in eval(expr, envir, enclos): object 'macru937_z23z22_plot' not foundcomparison_df <- merge(hs_macr_table[["data"]][["z23nosb_vs_z22nosb"]],
u937_table[["data"]][["z23nosb_vs_z22nosb"]],
by = "row.names")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'hs_macr_table' not foundmacru937_z23z22_plot <- plot_linear_scatter(comparison_df[, c("deseq_logfc.x", "deseq_logfc.y")])## Error in data.frame(df[, c(1, 2)]): object 'comparison_df' not foundmacru937_z23z22_plot$scatter## Error in eval(expr, envir, enclos): object 'macru937_z23z22_plot' not foundno_power_fact <- paste0(pData(hs_macr)[["donor"]], "_",
pData(hs_macr)[["condition"]])## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_macr' not foundhs_nopower <- set_expt_conditions(hs_macr, fact = no_power_fact)## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_macr' not foundhs_nopower <- subset_expt(hs_nopower, subset="macrophagezymodeme!='none'")## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'sampleNames': object 'hs_nopower' not foundhs_nopower_nosva_de <- all_pairwise(hs_nopower, model_batch = FALSE, filter = TRUE)## This DE analysis will perform all pairwise comparisons among:## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_nopower' not foundnopower_keepers <- list(
"d01_zymo" = c("d01infz23", "d01infz22"),
"d01_sbzymo" = c("d01infsbz23", "d01infsbz22"),
"d02_zymo" = c("d02infz23", "d02infz22"),
"d02_sbzymo" = c("d02infsbz23", "d02infsbz22"),
"d09_zymo" = c("d09infz23", "d09infz22"),
"d09_sbzymo" = c("d09infsbz23", "d09infsbz22"),
"d81_zymo" = c("d81infz23", "d81infz22"),
"d81_sbzymo" = c("d81infsbz23", "d81infsbz22"))
hs_nopower_nosva_table <- combine_de_tables(
hs_nopower_nosva_de, keepers = nopower_keepers,
excel = glue::glue("excel/hs_nopower_table-v{ver}.xlsx"))## Deleting the file excel/hs_nopower_table-v202212.xlsx before writing the tables.## Error in combine_de_tables(hs_nopower_nosva_de, keepers = nopower_keepers, : object 'hs_nopower_nosva_de' not found## extra_contrasts = extra)
hs_nopower_nosva_sig <- extract_significant_genes(
hs_nopower_nosva_table,
excel = glue::glue("excel/hs_nopower_nosva_sig-v{ver}.xlsx"))## Deleting the file excel/hs_nopower_nosva_sig-v202212.xlsx before writing the tables.## Error in extract_significant_genes(hs_nopower_nosva_table, excel = glue::glue("excel/hs_nopower_nosva_sig-v{ver}.xlsx")): object 'hs_nopower_nosva_table' not foundd01d02_zymo_nosva_comp <- merge(hs_nopower_nosva_table[["data"]][["d01_zymo"]],
hs_nopower_nosva_table[["data"]][["d02_zymo"]],
by="row.names")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'hs_nopower_nosva_table' not foundd0102_zymo_nosva_plot <- plot_linear_scatter(d01d02_zymo_nosva_comp[, c("deseq_logfc.x", "deseq_logfc.y")])## Error in data.frame(df[, c(1, 2)]): object 'd01d02_zymo_nosva_comp' not foundd0102_zymo_nosva_plot$scatter## Error in eval(expr, envir, enclos): object 'd0102_zymo_nosva_plot' not foundd0102_zymo_nosva_plot$correlation## Error in eval(expr, envir, enclos): object 'd0102_zymo_nosva_plot' not foundd0102_zymo_nosva_plot$lm_rsq## Error in eval(expr, envir, enclos): object 'd0102_zymo_nosva_plot' not foundd09d81_zymo_nosva_comp <- merge(hs_nopower_nosva_table[["data"]][["d09_zymo"]],
hs_nopower_nosva_table[["data"]][["d81_zymo"]],
by="row.names")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'hs_nopower_nosva_table' not foundd0981_zymo_nosva_plot <- plot_linear_scatter(d09d81_zymo_nosva_comp[, c("deseq_logfc.x", "deseq_logfc.y")])## Error in data.frame(df[, c(1, 2)]): object 'd09d81_zymo_nosva_comp' not foundd0981_zymo_nosva_plot$scatter## Error in eval(expr, envir, enclos): object 'd0981_zymo_nosva_plot' not foundd0981_zymo_nosva_plot$correlation## Error in eval(expr, envir, enclos): object 'd0981_zymo_nosva_plot' not foundd0981_zymo_nosva_plot$lm_rsq## Error in eval(expr, envir, enclos): object 'd0981_zymo_nosva_plot' not foundd01d81_zymo_nosva_comp <- merge(hs_nopower_nosva_table[["data"]][["d01_zymo"]],
hs_nopower_nosva_table[["data"]][["d81_zymo"]],
by="row.names")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'hs_nopower_nosva_table' not foundd0181_zymo_nosva_plot <- plot_linear_scatter(d01d81_zymo_nosva_comp[, c("deseq_logfc.x", "deseq_logfc.y")])## Error in data.frame(df[, c(1, 2)]): object 'd01d81_zymo_nosva_comp' not foundd0181_zymo_nosva_plot$scatter## Error in eval(expr, envir, enclos): object 'd0181_zymo_nosva_plot' not foundd0181_zymo_nosva_plot$correlation## Error in eval(expr, envir, enclos): object 'd0181_zymo_nosva_plot' not foundd0181_zymo_nosva_plot$lm_rsq## Error in eval(expr, envir, enclos): object 'd0181_zymo_nosva_plot' not foundupset_plots_nosva <- upsetr_sig(hs_nopower_nosva_sig, both=TRUE,
contrasts=c("d01_zymo", "d02_zymo", "d09_zymo", "d81_zymo"))## Error in upsetr_sig(hs_nopower_nosva_sig, both = TRUE, contrasts = c("d01_zymo", : object 'hs_nopower_nosva_sig' not foundupset_plots_nosva$up## Error in eval(expr, envir, enclos): object 'upset_plots_nosva' not foundupset_plots_nosva$down## Error in eval(expr, envir, enclos): object 'upset_plots_nosva' not foundupset_plots_nosva$both## Error in eval(expr, envir, enclos): object 'upset_plots_nosva' not found## The 7th element in the both groups list is the set shared among all donors.
## I don't feel like writing out x:y:z:a
groups <- upset_plots_nosva[["both_groups"]]## Error in eval(expr, envir, enclos): object 'upset_plots_nosva' not foundshared_genes <- attr(groups, "elements")[groups[[7]]] %>%
gsub(pattern = "^gene:", replacement = "")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'gsub': object 'groups' not foundshared_gp <- simple_gprofiler(shared_genes)## Error in "character" %in% class(sig_genes): object 'shared_genes' not foundshared_gp$pvalue_plots$MF## Error in eval(expr, envir, enclos): object 'shared_gp' not foundshared_gp$pvalue_plots$BP## Error in eval(expr, envir, enclos): object 'shared_gp' not foundshared_gp$pvalue_plots$REAC## Error in eval(expr, envir, enclos): object 'shared_gp' not foundshared_gp$pvalue_plots$WP## Error in eval(expr, envir, enclos): object 'shared_gp' not foundhs_nopower_sva_de <- all_pairwise(hs_nopower, model_batch = "svaseq", filter = TRUE)## This DE analysis will perform all pairwise comparisons among:## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_nopower' not foundnopower_keepers <- list(
"d01_zymo" = c("d01infz23", "d01infz22"),
"d01_sbzymo" = c("d01infsbz23", "d01infsbz22"),
"d02_zymo" = c("d02infz23", "d02infz22"),
"d02_sbzymo" = c("d02infsbz23", "d02infsbz22"),
"d09_zymo" = c("d09infz23", "d09infz22"),
"d09_sbzymo" = c("d09infsbz23", "d09infsbz22"),
"d81_zymo" = c("d81infz23", "d81infz22"),
"d81_sbzymo" = c("d81infsbz23", "d81infsbz22"))
hs_nopower_sva_table <- combine_de_tables(
hs_nopower_sva_de, keepers = nopower_keepers,
excel = glue::glue("excel/hs_nopower_table-v{ver}.xlsx"))## Error in combine_de_tables(hs_nopower_sva_de, keepers = nopower_keepers, : object 'hs_nopower_sva_de' not found## extra_contrasts = extra)
hs_nopower_sva_sig <- extract_significant_genes(
hs_nopower_sva_table,
excel = glue::glue("excel/hs_nopower_sva_sig-v{ver}.xlsx"))## Error in extract_significant_genes(hs_nopower_sva_table, excel = glue::glue("excel/hs_nopower_sva_sig-v{ver}.xlsx")): object 'hs_nopower_sva_table' not foundd01d02_zymo_sva_comp <- merge(hs_nopower_sva_table[["data"]][["d01_zymo"]],
hs_nopower_sva_table[["data"]][["d02_zymo"]],
by="row.names")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'hs_nopower_sva_table' not foundd0102_zymo_sva_plot <- plot_linear_scatter(d01d02_zymo_sva_comp[, c("deseq_logfc.x", "deseq_logfc.y")])## Error in data.frame(df[, c(1, 2)]): object 'd01d02_zymo_sva_comp' not foundd0102_zymo_sva_plot$scatter## Error in eval(expr, envir, enclos): object 'd0102_zymo_sva_plot' not foundd0102_zymo_sva_plot$correlation## Error in eval(expr, envir, enclos): object 'd0102_zymo_sva_plot' not foundd0102_zymo_sva_plot$lm_rsq## Error in eval(expr, envir, enclos): object 'd0102_zymo_sva_plot' not foundd09d81_zymo_sva_comp <- merge(hs_nopower_sva_table[["data"]][["d09_zymo"]],
hs_nopower_sva_table[["data"]][["d81_zymo"]],
by="row.names")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'hs_nopower_sva_table' not foundd0981_zymo_sva_plot <- plot_linear_scatter(d09d81_zymo_sva_comp[, c("deseq_logfc.x", "deseq_logfc.y")])## Error in data.frame(df[, c(1, 2)]): object 'd09d81_zymo_sva_comp' not foundd0981_zymo_sva_plot$scatter## Error in eval(expr, envir, enclos): object 'd0981_zymo_sva_plot' not foundd0981_zymo_sva_plot$correlation## Error in eval(expr, envir, enclos): object 'd0981_zymo_sva_plot' not foundd0981_zymo_sva_plot$lm_rsq## Error in eval(expr, envir, enclos): object 'd0981_zymo_sva_plot' not foundd01d81_zymo_sva_comp <- merge(hs_nopower_sva_table[["data"]][["d01_zymo"]],
hs_nopower_sva_table[["data"]][["d81_zymo"]],
by="row.names")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'merge': object 'hs_nopower_sva_table' not foundd0181_zymo_sva_plot <- plot_linear_scatter(d01d81_zymo_sva_comp[, c("deseq_logfc.x", "deseq_logfc.y")])## Error in data.frame(df[, c(1, 2)]): object 'd01d81_zymo_sva_comp' not foundd0181_zymo_sva_plot$scatter## Error in eval(expr, envir, enclos): object 'd0181_zymo_sva_plot' not foundd0181_zymo_sva_plot$correlation## Error in eval(expr, envir, enclos): object 'd0181_zymo_sva_plot' not foundd0181_zymo_sva_plot$lm_rsq## Error in eval(expr, envir, enclos): object 'd0181_zymo_sva_plot' not foundupset_plots_sva <- upsetr_sig(hs_nopower_sva_sig, both=TRUE,
contrasts=c("d01_zymo", "d02_zymo", "d09_zymo", "d81_zymo"))## Error in upsetr_sig(hs_nopower_sva_sig, both = TRUE, contrasts = c("d01_zymo", : object 'hs_nopower_sva_sig' not foundupset_plots_sva$up## Error in eval(expr, envir, enclos): object 'upset_plots_sva' not foundupset_plots_sva$down## Error in eval(expr, envir, enclos): object 'upset_plots_sva' not foundupset_plots_sva$both## Error in eval(expr, envir, enclos): object 'upset_plots_sva' not found## The 7th element in the both groups list is the set shared among all donors.
## I don't feel like writing out x:y:z:a
groups <- upset_plots_sva[["both_groups"]]## Error in eval(expr, envir, enclos): object 'upset_plots_sva' not foundshared_genes <- attr(groups, "elements")[groups[[7]]] %>%
gsub(pattern = "^gene:", replacement = "")## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'gsub': object 'groups' not foundshared_gp <- simple_gprofiler(shared_genes)## Error in "character" %in% class(sig_genes): object 'shared_genes' not foundshared_gp$pvalue_plots$MF## Error in eval(expr, envir, enclos): object 'shared_gp' not foundshared_gp$pvalue_plots$BP## Error in eval(expr, envir, enclos): object 'shared_gp' not foundshared_gp$pvalue_plots$REAC## Error in eval(expr, envir, enclos): object 'shared_gp' not foundshared_gp$pvalue_plots$WP## Error in eval(expr, envir, enclos): object 'shared_gp' not founddonor_de <- all_pairwise(hs_donors, model_batch="svaseq", filter=TRUE)## This DE analysis will perform all pairwise comparisons among:## Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'pData': object 'hs_donors' not founddonor_table <- combine_de_tables(
donor_de,
excel=glue::glue("excel/donor_tables-v{ver}.xlsx"))## Deleting the file excel/donor_tables-v202212.xlsx before writing the tables.## Error in combine_de_tables(donor_de, excel = glue::glue("excel/donor_tables-v{ver}.xlsx")): object 'donor_de' not foundThe final contrast in this list is interesting because it depends on the extra contrasts applied to the all_pairwise() above. In my way of thinking, the primary comparisons to consider are either cross-drug or cross-strain, but not both. However I think in at least a few instances Olga is interested in strain+drug / uninfected+nodrug.
Now let us write out the xlsx file containing the above contrasts. The file with the suffix _table-version will therefore contain all genes and the file with the suffix _sig-version will contain only those deemed significant via our default criteria of DESeq2 |logFC| >= 1.0 and adjusted p-value <= 0.05.
hs_macr_table <- combine_de_tables(
hs_macr_de,
keepers = tmrc2_human_keepers,
excel=glue::glue("excel/macrophage_human_table-v{ver}.xlsx"))## Error in combine_de_tables(hs_macr_de, keepers = tmrc2_human_keepers, : object 'hs_macr_de' not foundhs_macr_sig <- extract_significant_genes(
hs_macr_table,
excel=glue::glue("excel/macrophage_human_sig-v{ver}.xlsx"))## Error in extract_significant_genes(hs_macr_table, excel = glue::glue("excel/macrophage_human_sig-v{ver}.xlsx")): object 'hs_macr_table' not foundu937_table <- combine_de_tables(
u937_de,
keepers = tmrc2_human_keepers,
excel=glue::glue("excel/u937_human_table-v{ver}.xlsx"))## Error in combine_de_tables(u937_de, keepers = tmrc2_human_keepers, excel = glue::glue("excel/u937_human_table-v{ver}.xlsx")): object 'u937_de' not foundu937_sig <- extract_significant_genes(
u937_table,
excel=glue::glue("excel/u937_human_sig-v{ver}.xlsx"))## Error in extract_significant_genes(u937_table, excel = glue::glue("excel/u937_human_sig-v{ver}.xlsx")): object 'u937_table' not foundI decided to make one initially small, but I think quickly big change to the organization of this document: I am moving the GSEA searches up to immediately after the DE. I will then move the plots of the gprofiler results to immediately after the various volcano plots so that it is easier to interpret them.
all_gp <- all_gprofiler(hs_macr_sig)## Error in all_gprofiler(hs_macr_sig): object 'hs_macr_sig' not foundOne suggestion I received recently was to set the axes for these volcano plots to be static rather than let ggplot choose its own. I am assuming this is only relevant for pairs of contrasts, but that might not be true.
z23nosb_vs_uninf_volcano <- plot_volcano_de(
table = hs_macrophage_table[["data"]][["z23nosb_vs_uninf"]],
fc_col = "deseq_logfc", p_col = "deseq_adjp",
shapes_by_state = FALSE, color_by = "fc", label = 10, label_column = "hgncsymbol")## Error in is.data.frame(x): object 'hs_macrophage_table' not foundplotly::ggplotly(z23nosb_vs_uninf_volcano$plot)## Error in plotly::ggplotly(z23nosb_vs_uninf_volcano$plot): object 'z23nosb_vs_uninf_volcano' not foundz22nosb_vs_uninf_volcano <- plot_volcano_de(
table = hs_macrophage_table[["data"]][["z22nosb_vs_uninf"]],
fc_col = "deseq_logfc", p_col = "deseq_adjp",
shapes_by_state = FALSE, color_by = "fc", label = 10, label_column = "hgncsymbol")## Error in is.data.frame(x): object 'hs_macrophage_table' not foundplotly::ggplotly(z22nosb_vs_uninf_volcano$plot)## Error in plotly::ggplotly(z22nosb_vs_uninf_volcano$plot): object 'z22nosb_vs_uninf_volcano' not foundz23nosb_vs_uninf_volcano$plot +
xlim(-10, 25) +
ylim(0, 40)## Error in eval(expr, envir, enclos): object 'z23nosb_vs_uninf_volcano' not foundpp(file="images/z23_uninf_reactome_up.png", image=all_gp[["z23nosb_vs_uninf_up"]][["pvalue_plots"]][["REAC"]], height=12, width=9)## Error in pp(file = "images/z23_uninf_reactome_up.png", image = all_gp[["z23nosb_vs_uninf_up"]][["pvalue_plots"]][["REAC"]], : object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_uninf_up"]][["pvalue_plots"]][["KEGG"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## KEGG, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_uninf_up"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_uninf_up"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_uninf_up"]][["pvalue_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## WikiPathways, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_uninf_up"]][["interactive_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not foundall_gp[["z23nosb_vs_uninf_down"]][["pvalue_plots"]][["REAC"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z23nosb_vs_uninf_down"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z23nosb_vs_uninf_down"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, down.z22nosb_vs_uninf_volcano$plot +
xlim(-10, 25) +
ylim(0, 40)## Error in eval(expr, envir, enclos): object 'z22nosb_vs_uninf_volcano' not foundpp(file="images/z22_uninf_reactome_up.png", image=all_gp[["z22nosb_vs_uninf_up"]][["pvalue_plots"]][["REAC"]], height=12, width=9)## Error in pp(file = "images/z22_uninf_reactome_up.png", image = all_gp[["z22nosb_vs_uninf_up"]][["pvalue_plots"]][["REAC"]], : object 'all_gp' not found## Reactome, zymodeme2.2 without drug vs. uninfected without drug, up.
all_gp[["z22nosb_vs_uninf_up"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.2 without drug vs. uninfected without drug, up.
all_gp[["z22nosb_vs_uninf_up"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.2 without drug vs. uninfected without drug, up.
all_gp[["z22nosb_vs_uninf_up"]][["pvalue_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## WikiPathways, zymodeme2.2 without drug vs. uninfected without drug, up.
all_gp[["z22nosb_vs_uninf_down"]][["pvalue_plots"]][["REAC"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## Reactome, zymodeme2.2 without drug vs. uninfected without drug, down.
all_gp[["z22nosb_vs_uninf_down"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.2 without drug vs. uninfected without drug, down.
all_gp[["z22nosb_vs_uninf_down"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, down.Check that my perception of the number of significant up/down genes matches what the table/venn says.
shared <- Vennerable::Venn(list("drug" = rownames(hs_macrophage_sig[["deseq"]][["ups"]][["z23sb_vs_uninf"]]),
"nodrug" = rownames(hs_macrophage_sig[["deseq"]][["ups"]][["z23nosb_vs_uninf"]])))## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'hs_macrophage_sig' not foundpp(file="images/z23_vs_uninf_venn_up.png")
Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not founddev.off()## png
## 2Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not found## I see 910 z23sb/uninf and 670 no z23nosb/uninf genes in the venn diagram.
length(shared@IntersectionSets[["10"]]) + length(shared@IntersectionSets[["11"]])## Error in eval(expr, envir, enclos): object 'shared' not founddim(hs_macrophage_sig[["deseq"]][["ups"]][["z23sb_vs_uninf"]])## Error in eval(expr, envir, enclos): object 'hs_macrophage_sig' not foundshared <- Vennerable::Venn(list("drug" = rownames(hs_macrophage_sig[["deseq"]][["ups"]][["z22sb_vs_uninf"]]),
"nodrug" = rownames(hs_macrophage_sig[["deseq"]][["ups"]][["z22nosb_vs_uninf"]])))## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'hs_macrophage_sig' not foundpp(file="images/z22_vs_uninf_venn_up.png")
Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not founddev.off()## png
## 2Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not foundlength(shared@IntersectionSets[["10"]]) + length(shared@IntersectionSets[["11"]])## Error in eval(expr, envir, enclos): object 'shared' not founddim(hs_macrophage_sig[["deseq"]][["ups"]][["z22sb_vs_uninf"]])## Error in eval(expr, envir, enclos): object 'hs_macrophage_sig' not foundNote to self: There is an error in my volcano plot code which takes effect when the numerator and denominator of the all_pairwise contrasts are different than those in combine_de_tables. It is putting the ups/downs on the correct sides of the plot, but calling the down genes ‘up’ and vice-versa. The reason for this is that I did a check for this happening, but used the wrong argument to handle it.
A likely bit of text for these volcano plots:
The set of genes differentially expressed between the zymodeme 2.3 and uninfected samples without druge treatment was quantified with DESeq2 and included surrogate estimates from SVA. Given the criteria of significance of a abs(logFC) >= 1.0 and false discovery rate adjusted p-value <= 0.05, 670 genes were observed as significantly increased between the infected and uninfected samples and 386 were observed as decreased. The most increased genes from the uninfected samples include some which are potentially indicative of a strong innate immune response and the inflammatory response.
In contrast, when the set of genes differentially expressed between the zymodeme 2.2 and uninfected samples was visualized, only 7 genes were observed as decreased and 435 increased. The inflammatory response was significantly less apparent in this set, but instead included genes related to transporter activity and oxidoreductases.
An orthogonal comparison to that performed above is to directly compare the zymodeme 2.3 and 2.2 samples with and without antimonial treatment.
z23nosb_vs_z22nosb_volcano <- plot_volcano_de(
table = hs_macrophage_table[["data"]][["z23nosb_vs_z22nosb"]],
fc_col = "deseq_logfc", p_col = "deseq_adjp",
shapes_by_state = FALSE, color_by = "fc", label = 10, label_column = "hgncsymbol")## Error in is.data.frame(x): object 'hs_macrophage_table' not foundplotly::ggplotly(z23nosb_vs_z22nosb_volcano$plot)## Error in plotly::ggplotly(z23nosb_vs_z22nosb_volcano$plot): object 'z23nosb_vs_z22nosb_volcano' not foundz23sb_vs_z22sb_volcano <- plot_volcano_de(
table = hs_macrophage_table[["data"]][["z23sb_vs_z22sb"]],
fc_col = "deseq_logfc", p_col = "deseq_adjp",
shapes_by_state = FALSE, color_by = "fc", label = 10, label_column = "hgncsymbol")## Error in is.data.frame(x): object 'hs_macrophage_table' not foundplotly::ggplotly(z23sb_vs_z22sb_volcano$plot)## Error in plotly::ggplotly(z23sb_vs_z22sb_volcano$plot): object 'z23sb_vs_z22sb_volcano' not foundz23nosb_vs_z22nosb_volcano$plot +
xlim(-10, 10) +
ylim(0, 60)## Error in eval(expr, envir, enclos): object 'z23nosb_vs_z22nosb_volcano' not foundpp(file="images/z23nosb_vs_z22nosb_reactome_up.png", image=all_gp[["z23nosb_vs_z22nosb_up"]][["pvalue_plots"]][["REAC"]], height=12, width=9)## Error in pp(file = "images/z23nosb_vs_z22nosb_reactome_up.png", image = all_gp[["z23nosb_vs_z22nosb_up"]][["pvalue_plots"]][["REAC"]], : object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_z22nosb_up"]][["pvalue_plots"]][["KEGG"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## KEGG, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_z22nosb_up"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_z22nosb_up"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_z22nosb_up"]][["pvalue_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## WikiPathways, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23nosb_vs_z22nosb_up"]][["interactive_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not foundall_gp[["z23nosb_vs_z22nosb_down"]][["pvalue_plots"]][["REAC"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z23nosb_vs_z22nosb_down"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z23nosb_vs_z22nosb_down"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, down.z23sb_vs_z22sb_volcano$plot +
xlim(-10, 10) +
ylim(0, 60)## Error in eval(expr, envir, enclos): object 'z23sb_vs_z22sb_volcano' not foundpp(file="images/z23sb_vs_z22sb_reactome_up.png", image=all_gp[["z23sb_vs_z22sb_up"]][["pvalue_plots"]][["REAC"]], height=12, width=9)## Error in pp(file = "images/z23sb_vs_z22sb_reactome_up.png", image = all_gp[["z23sb_vs_z22sb_up"]][["pvalue_plots"]][["REAC"]], : object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z22sb_up"]][["pvalue_plots"]][["KEGG"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## KEGG, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z22sb_up"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z22sb_up"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z22sb_up"]][["pvalue_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## WikiPathways, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z22sb_up"]][["interactive_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not foundall_gp[["z23sb_vs_z22sb_down"]][["pvalue_plots"]][["REAC"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z23sb_vs_z22sb_down"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z23sb_vs_z22sb_down"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, down.shared <- Vennerable::Venn(list("drug" = rownames(hs_macrophage_sig[["deseq"]][["ups"]][["z23sb_vs_z22sb"]]),
"nodrug" = rownames(hs_macrophage_sig[["deseq"]][["ups"]][["z23nosb_vs_z22nosb"]])))## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'hs_macrophage_sig' not foundpp(file="images/drug_nodrug_venn_up.png")
Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not founddev.off()## png
## 2Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not foundshared <- Vennerable::Venn(list("drug" = rownames(hs_macrophage_sig[["deseq"]][["downs"]][["z23sb_vs_z22sb"]]),
"nodrug" = rownames(hs_macrophage_sig[["deseq"]][["downs"]][["z23nosb_vs_z22nosb"]])))## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'hs_macrophage_sig' not foundpp(file="images/drug_nodrug_venn_down.png")
Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not founddev.off()## png
## 2A slightly different way of looking at the differences between the two zymodeme infections is to directly compare the infected samples with and without drug. Thus, when a volcano plot showing the comparison of the zymodeme 2.3 vs. 2.2 samples was plotted, 484 genes were observed as increased and 422 decreased; these groups include many of the same inflammatory (up) and membrane (down) genes.
Similar patterns were observed when the antimonial was included. Thus, when a Venn diagram of the two sets of increased genes was plotted, a significant number of the genes was observed as increased (313) and decreased (244) in both the untreated and antimonial treated samples.
Another likely question is to directly compare the treated vs untreated samples for each zymodeme infection in order to visualize the effects of antimonial.
z23sb_vs_z23nosb_volcano <- plot_volcano_de(
table = hs_macrophage_table[["data"]][["z23sb_vs_z23nosb"]],
fc_col = "deseq_logfc", p_col = "deseq_adjp",
shapes_by_state = FALSE, color_by = "fc", label = 10, label_column = "hgncsymbol")## Error in is.data.frame(x): object 'hs_macrophage_table' not foundplotly::ggplotly(z23sb_vs_z23nosb_volcano$plot)## Error in plotly::ggplotly(z23sb_vs_z23nosb_volcano$plot): object 'z23sb_vs_z23nosb_volcano' not foundz22sb_vs_z22nosb_volcano <- plot_volcano_de(
table = hs_macrophage_table[["data"]][["z22sb_vs_z22nosb"]],
fc_col = "deseq_logfc", p_col = "deseq_adjp",
shapes_by_state = FALSE, color_by = "fc", label = 10, label_column = "hgncsymbol")## Error in is.data.frame(x): object 'hs_macrophage_table' not foundplotly::ggplotly(z22sb_vs_z22nosb_volcano$plot)## Error in plotly::ggplotly(z22sb_vs_z22nosb_volcano$plot): object 'z22sb_vs_z22nosb_volcano' not foundz23sb_vs_z23nosb_volcano$plot +
xlim(-8, 8) +
ylim(0, 210)## Error in eval(expr, envir, enclos): object 'z23sb_vs_z23nosb_volcano' not foundpp(file="images/z23sb_vs_z23nosb_reactome_up.png",
image=all_gp[["z23sb_vs_z23nosb_up"]][["pvalue_plots"]][["REAC"]], height=12, width=9)## Error in pp(file = "images/z23sb_vs_z23nosb_reactome_up.png", image = all_gp[["z23sb_vs_z23nosb_up"]][["pvalue_plots"]][["REAC"]], : object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z23nosb_up"]][["pvalue_plots"]][["KEGG"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## KEGG, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z23nosb_up"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z23nosb_up"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z23nosb_up"]][["pvalue_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## WikiPathways, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z23sb_vs_z23nosb_up"]][["interactive_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not foundall_gp[["z23sb_vs_z23nosb_down"]][["pvalue_plots"]][["REAC"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z23sb_vs_z23nosb_down"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z23sb_vs_z23nosb_down"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, down.z22sb_vs_z22nosb_volcano$plot +
xlim(-8, 8) +
ylim(0, 210)## Error in eval(expr, envir, enclos): object 'z22sb_vs_z22nosb_volcano' not foundpp(file="images/z22sb_vs_z22nosb_reactome_up.png",
image=all_gp[["z22sb_vs_z22nosb_up"]][["pvalue_plots"]][["REAC"]], height=12, width=9)## Error in pp(file = "images/z22sb_vs_z22nosb_reactome_up.png", image = all_gp[["z22sb_vs_z22nosb_up"]][["pvalue_plots"]][["REAC"]], : object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z22sb_vs_z22nosb_up"]][["pvalue_plots"]][["KEGG"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## KEGG, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z22sb_vs_z22nosb_up"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z22sb_vs_z22nosb_up"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z22sb_vs_z22nosb_up"]][["pvalue_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## WikiPathways, zymodeme2.3 without drug vs. uninfected without drug, up.
all_gp[["z22sb_vs_z22nosb_up"]][["interactive_plots"]][["WP"]]## Error in eval(expr, envir, enclos): object 'all_gp' not foundall_gp[["z22sb_vs_z22nosb_down"]][["pvalue_plots"]][["REAC"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## Reactome, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z22sb_vs_z22nosb_down"]][["pvalue_plots"]][["MF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## MF, zymodeme2.3 without drug vs. uninfected without drug, down.
all_gp[["z22sb_vs_z22nosb_down"]][["pvalue_plots"]][["TF"]]## Error in eval(expr, envir, enclos): object 'all_gp' not found## TF, zymodeme2.3 without drug vs. uninfected without drug, down.shared <- Vennerable::Venn(list("z23" = rownames(hs_macrophage_sig[["deseq"]][["ups"]][["z23sb_vs_z23nosb"]]),
"z22" = rownames(hs_macrophage_sig[["deseq"]][["ups"]][["z22sb_vs_z22nosb"]])))## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'hs_macrophage_sig' not foundpp(file="images/z23_z22_drug_venn_up.png")
Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not founddev.off()## png
## 2Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not foundshared <- Vennerable::Venn(list("z23" = rownames(hs_macrophage_sig[["deseq"]][["downs"]][["z23sb_vs_z23nosb"]]),
"z22" = rownames(hs_macrophage_sig[["deseq"]][["downs"]][["z22sb_vs_z22nosb"]])))## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'rownames': object 'hs_macrophage_sig' not foundpp(file="images/z23_z22_drug_venn_down.png")
Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not founddev.off()## png
## 2Vennerable::plot(shared)## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'shared' not foundNote: I am settig the x and y-axis boundaries by allowing the plotter to pick its own axis the first time, writing down the ranges I observe, and then setting them to the largest of the pair. It is therefore possible that I missed one or more genes which lies outside that range.
The previous plotted contrasts sought to show changes between the two strains z2.3 and z2.2. Conversely, the previous volcano plots seek to directly compare each strain before/after drug treatment.
lp_macrophage_de <- all_pairwise(lp_macrophage,
model_batch="svaseq", filter=TRUE)## This DE analysis will perform all pairwise comparisons among:##
## z2.2 z2.3
## 11 9## This analysis will include surrogate estimates from: svaseq.## This will pre-filter the input data using normalize_expt's: TRUE argument.## Removing 0 low-count genes (8541 remaining).## Setting 134 low elements to zero.## transform_counts: Found 134 values equal to 0, adding 1 to the matrix.## Finished running DE analyses, collecting outputs.## Comparing analyses.tmrc2_parasite_keepers <- list(
"z23nosb_vs_z22nosb" = c("z23", "z22"))
lp_macrophage_table <- combine_de_tables(
lp_macrophage_de, keepers = tmrc2_parasite_keepers,
excel=glue::glue("excel/macrophage_parasite_infection_de-v{ver}.xlsx"))## Starting combine_extracted_plots() with do_inverse as: FALSE.## Plotting volcano plot of the DE results of z23_vs_z22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of z23_vs_z22 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of z23_vs_z22 according to the columns: logFC and adj.P.Val using the expressionset colors.lp_macrophage_sig <- extract_significant_genes(
lp_macrophage_table,
excel=glue::glue("excel/macrophage_parasite_sig-v{ver}.xlsx"))## Plotting volcano plot of the DE results of z23_vs_z22 according to the columns: logFC and adj.P.Val using the expressionset colors.## Plotting volcano plot of the DE results of z23_vs_z22 according to the columns: logFC and FDR using the expressionset colors.## Plotting volcano plot of the DE results of z23_vs_z22 according to the columns: logFC and adj.P.Val using the expressionset colors.pp(file="images/lp_macrophage_z23_z22.png",
image=lp_macrophage_table[["plots"]][["z23nosb_vs_z22nosb"]][["deseq_vol_plots"]][["plot"]])## Warning in pp(file = "images/lp_macrophage_z23_z22.png", image =
## lp_macrophage_table[["plots"]][["z23nosb_vs_z22nosb"]][["deseq_vol_plots"]][["plot"]]):
## There is no device to shut down.up_genes <- lp_macrophage_sig[["deseq"]][["ups"]][[1]]
dim(up_genes)## [1] 47 58down_genes <- lp_macrophage_sig[["deseq"]][["downs"]][[1]]
dim(down_genes)## [1] 88 58lp_z23sb_vs_z22sb_volcano <- plot_volcano_de(
table = lp_macrophage_table[["data"]][["z23nosb_vs_z22nosb"]],
fc_col = "deseq_logfc", p_col = "deseq_adjp",
shapes_by_state = FALSE, color_by = "fc", label = 10, label_column = "hgncsymbol")## Error in plot_volcano_de(table = lp_macrophage_table[["data"]][["z23nosb_vs_z22nosb"]], : object 'color_list' not foundplotly::ggplotly(lp_z23sb_vs_z22sb_volcano$plot)## Error in plotly::ggplotly(lp_z23sb_vs_z22sb_volcano$plot): object 'lp_z23sb_vs_z22sb_volcano' not foundlp_z23nosb_vs_z22nosb_volcano$plot## Error in eval(expr, envir, enclos): object 'lp_z23nosb_vs_z22nosb_volcano' not foundup_goseq <- simple_goseq(up_genes, go_db=lp_go, length_db=lp_lengths)## Found 16 go_db genes and 47 length_db genes out of 47.## Testing that go categories are defined.## Removing undefined categories.## Gathering synonyms.## Gathering category definitions.## The score column is null, defaulting to score.## Possible columns are:## [1] "category" "over_represented_pvalue"
## [3] "under_represented_pvalue" "numDEInCat"
## [5] "numInCat" "term"
## [7] "ontology" "qvalue"## The over_represented_pvalue column is null, defaulting to score.## Possible columns are:## [1] "term" "pvalue" "score" "num_de" "num_cat"## The score column is null, defaulting to score.## Possible columns are:## [1] "category" "over_represented_pvalue"
## [3] "under_represented_pvalue" "numDEInCat"
## [5] "numInCat" "term"
## [7] "ontology" "qvalue"## The over_represented_pvalue column is null, defaulting to score.## Possible columns are:## [1] "term" "pvalue" "score" "num_de" "num_cat"## The score column is null, defaulting to score.## Possible columns are:## [1] "category" "over_represented_pvalue"
## [3] "under_represented_pvalue" "numDEInCat"
## [5] "numInCat" "term"
## [7] "ontology" "qvalue"## The over_represented_pvalue column is null, defaulting to score.## Possible columns are:## [1] "term" "pvalue" "score" "num_de" "num_cat"## View categories over represented in the 2.3 samples
up_goseq$pvalue_plots$bpp_plot_over
down_goseq <- simple_goseq(down_genes, go_db=lp_go, length_db=lp_lengths)## Found 28 go_db genes and 88 length_db genes out of 88.## Testing that go categories are defined.## Removing undefined categories.## Gathering synonyms.## Gathering category definitions.## The score column is null, defaulting to score.## Possible columns are:## [1] "category" "over_represented_pvalue"
## [3] "under_represented_pvalue" "numDEInCat"
## [5] "numInCat" "term"
## [7] "ontology" "qvalue"## The over_represented_pvalue column is null, defaulting to score.## Possible columns are:## [1] "term" "pvalue" "score" "num_de" "num_cat"## The score column is null, defaulting to score.## Possible columns are:## [1] "category" "over_represented_pvalue"
## [3] "under_represented_pvalue" "numDEInCat"
## [5] "numInCat" "term"
## [7] "ontology" "qvalue"## The over_represented_pvalue column is null, defaulting to score.## Possible columns are:## [1] "term" "pvalue" "score" "num_de" "num_cat"## The score column is null, defaulting to score.## Possible columns are:## [1] "category" "over_represented_pvalue"
## [3] "under_represented_pvalue" "numDEInCat"
## [5] "numInCat" "term"
## [7] "ontology" "qvalue"## The over_represented_pvalue column is null, defaulting to score.## Possible columns are:## [1] "term" "pvalue" "score" "num_de" "num_cat"## View categories over represented in the 2.2 samples
down_goseq$pvalue_plots$bpp_plot_over
hs_infected <- subset_expt(hs_macrophage, subset="macrophagetreatment!='uninf'") %>%
subset_expt(subset="macrophagetreatment!='uninf_sb'")
hs_gsva_c2 <- simple_gsva(hs_infected)
hs_gsva_c2_meta <- get_msigdb_metadata(hs_gsva_c2, msig_xml="reference/msigdb_v7.2.xml")
hs_gsva_c2_sig <- get_sig_gsva_categories(hs_gsva_c2_meta, excel = "excel/hs_macrophage_gsva_c2_sig.xlsx")
hs_gsva_c2_sig$raw_plot
hs_gsva_c7 <- simple_gsva(hs_infected, signature_category = "c7")
hs_gsva_c7_meta <- get_msigdb_metadata(hs_gsva_c7, msig_xml="reference/msigdb_v7.2.xml")4
hs_gsva_c7_sig <- get_sig_gsva_categories(hs_gsva_c7, excel = "excel/hs_macrophage_gsva_c7_sig.xlsx")
hs_gsva_c7_sig$raw_plot## Error: <text>:9:89: unexpected numeric constant
## 8: hs_gsva_c7 <- simple_gsva(hs_infected, signature_category = "c7")
## 9: hs_gsva_c7_meta <- get_msigdb_metadata(hs_gsva_c7, msig_xml="reference/msigdb_v7.2.xml")4
## ^Two reasons: Najib loves him some PCA, this uses wikipathways, which is something I think is neat.
Ok, I spent some time looking through the code and I have some problems with some of the design decisions.
Most importantly, it requires a data.frame() which has the following format:
But when I think about it I think I get the idea, they want to be able to do modelling stuff more easily with response factors.
library(pathwayPCA)
library(rWikiPathways)
downloaded <- downloadPathwayArchive(organism = "Homo sapiens", format = "gmt")
data_path <- system.file("extdata", package="pathwayPCA")
wikipathways <- read_gmt(paste0(data_path, "/wikipathways_human_symbol.gmt"), description=TRUE)
expt <- subset_expt(hs_macrophage, subset="macrophagetreatment!='uninf'") %>%
subset_expt(subset="macrophagetreatment!='uninf_sb'")
expt <- set_expt_conditions(expt, fact="macrophagezymodeme")
symbol_vector <- fData(expt)[[symbol_column]]
names(symbol_vector) <- rownames(fData(expt))
symbol_df <- as.data.frame(symbol_vector)
assay_df <- merge(symbol_df, as.data.frame(exprs(expt)), by = "row.names")
assay_df[["Row.names"]] <- NULL
rownames(assay_df) <- make.names(assay_df[["symbol_vector"]], unique = TRUE)
assay_df[["symbol_vector"]] <- NULL
assay_df <- as.data.frame(t(assay_df))
assay_df[["SampleID"]] <- rownames(assay_df)
assay_df <- dplyr::select(assay_df, "SampleID", everything())
factor_df <- as.data.frame(pData(expt))
factor_df[["SampleID"]] <- rownames(factor_df)
factor_df <- dplyr::select(factor_df, "SampleID", everything())
factor_df <- factor_df[, c("SampleID", factors)]
tt <- CreateOmics(
assayData_df = assay_df,
pathwayCollection_ls = wikipathways,
response = factor_df,
respType = "categorical",
minPathSize=5)
super <- AESPCA_pVals(
object = tt,
numPCs = 2,
parallel = FALSE,
numCores = 8,
numReps = 2,
adjustment = "BH")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))
}## If you wish to reproduce this exact build of hpgltools, invoke the following:## > git clone http://github.com/abelew/hpgltools.git## > git reset 911e7d4beebdc73267ec4be631a305574289efd3## This is hpgltools commit: Tue Jan 17 10:36:44 2023 -0500: 911e7d4beebdc73267ec4be631a305574289efd3## Saving to tmrc2_macrophage_visualization_202212.rda.xztmp <- loadme(filename = savefile)