At this point, I am reasonably sure that the data is not crazytown or replete with difficult to assay batch effects. We have (I think) a reasonable factor in the experimental design to include as batch, so I will allow my differential expression toys to use that.
Lets see what happens!
## Reminder: isc_test just has batches a vs. b (old vs. new)
## For this first attempt, put batch in the model and only work with batches named 'a' and 'b'
## a_isc_test_condbatch <- sm(all_pairwise(isc_test))
## For a second test, do the more complex a/b/c batches and try putting batch in model.
## b_isc_all_condbatch <- sm(all_pairwise(isc_all))
## The prettiest pca plots were obtained when using (f)sva, so try those next.
## c_isc_test_sva <- sm(all_pairwise(isc_test, model_batch="sva"))
## d_isc_all_sva <- sm(all_pairwise(isc_all, model_batch="sva"))
## e_isc_test_fsva <- sm(all_pairwise(isc_test, model_batch="fsva"))
## f_isc_all_fsva <- sm(all_pairwise(isc_all, model_batch="fsva"))
## Also do one run of each with only the new data.
g_isc_new_condbatch <- sm(all_pairwise(isc_new))## Error in normalize_expt(input, filter = TRUE, batch = FALSE, transform = "log2", : object 'isc_new' not found## h_isc_new_sva <- sm(all_pairwise(isc_new, model_batch="sva"))
## i_isc_new_fsva <- sm(all_pairwise(isc_new, model_batch="fsva"))I’m going to create a series of excel sheets to compare/contrast these results and therefore will save each excel with a limited number of contrasts.
inf_uninf <- list("gut_infuninf" = c("infected_gut","uninfected_gut"),
"sal_infuninf" = c("infected_salivary","uninfected_salivary"))
salv_gut <- list("inf_salvgut" = c("infected_salivary","infected_gut"),
"uninf_salvgut" = c("uninfected_salivary","uninfected_gut"))I have thus far done 9 types of contrats of this data. Lets generate some appropriate reports in the hopes of getting an understanding of which did/didn’t work.
##a_infuninf <- combine_de_tables(a_isc_test_condbatch, keepers=inf_uninf, excel=FALSE)
##a_salvgut <- combine_de_tables(a_isc_test_condbatch, keepers=salv_gut, excel=FALSE)
##b_infuninf <- combine_de_tables(b_isc_all_condbatch, keepers=inf_uninf, excel=FALSE)
##b_salvgut <- combine_de_tables(b_isc_all_condbatch, keepers=salv_gut, excel=FALSE)
##c_infuninf <- combine_de_tables(c_isc_test_sva, keepers=inf_uninf, excel=FALSE)
##c_salvgut <- combine_de_tables(c_isc_test_sva, keepers=salv_gut, excel=FALSE)
##d_infuninf <- combine_de_tables(d_isc_all_sva, keepers=inf_uninf, excel=FALSE)
##d_salvgut <- combine_de_tables(d_isc_all_sva, keepers=salv_gut, excel=FALSE)
##e_infuninf <- combine_de_tables(e_isc_test_fsva, keepers=inf_uninf, excel=FALSE)
##e_salvgut <- combine_de_tables(e_isc_test_fsva, keepers=salv_gut, excel=FALSE)
##f_infuninf <- combine_de_tables(f_isc_all_fsva, keepers=inf_uninf, excel=FALSE)
##f_salvgut <- combine_de_tables(f_isc_all_fsva, keepers=salv_gut, excel=FALSE)
##h_infuninf <- combine_de_tables(h_isc_new_sva, keepers=inf_uninf, excel=FALSE)
##h_salvgut <- combine_de_tables(h_isc_new_sva, keepers=salv_gut, excel=FALSE)
##i_infuninf <- combine_de_tables(i_isc_new_fsva, keepers=inf_uninf, excel=FALSE)
##i_salvgut <- combine_de_tables(i_isc_new_fsva, keepers=salv_gut, excel=FALSE)
## Perhaps extracting significant genes will be helpful
##a_infuninf_sig <- extract_significant_genes(a_infuninf, excel="excel/a_infuninf_sig.xlsx")
##a_salvgut_sig <- extract_significant_genes(a_savlgut, keepers=salv_gut, excel=FALSE)
##b_infuninf_sig <- extract_significant_genes(b_infuninf, keepers=inf_uninf, excel=FALSE)
##b_salvgut_sig <- extract_significant_genes(b_salvgut, keepers=salv_gut, excel=FALSE)
##c_infuninf_sig <- extract_significant_genes(c_infuninf, keepers=inf_uninf, excel=FALSE)
##c_salvgut_sig <- extract_significant_genes(c_salvgut, keepers=salv_gut, excel=FALSE)
##d_infuninf_sig <- extract_significant_genes(d_infuninf, keepers=inf_uninf, excel=FALSE)
##d_salvgut_sig <- extract_significant_genes(d_salvgut, keepers=salv_gut, excel=FALSE)
##e_infuninf_sig <- extract_significant_genes(e_infuninf, keepers=inf_uninf, excel=FALSE)
##e_salvgut_sig <- extract_significant_genes(e_salvgut, keepers=salv_gut, excel=FALSE)
##f_infuninf_sig <- extract_significant_genes(f_infuninf, keepers=inf_uninf, excel=FALSE)
##f_salvgut_sig <- extract_significant_genes(f_salvgut, keepers=salv_gut, excel=FALSE)
g_infuninf <- sm(combine_de_tables(g_isc_new_condbatch, keepers=inf_uninf,
excel=paste0("excel/g_isc_new_condbatch_tables_infuninf-", ver, ".xlsx")))## Error in combine_de_tables(g_isc_new_condbatch, keepers = inf_uninf, excel = paste0("excel/g_isc_new_condbatch_tables_infuninf-", : object 'g_isc_new_condbatch' not foundg_salvgut <- sm(combine_de_tables(g_isc_new_condbatch, keepers=salv_gut,
excel=paste0("excel/g_isc_new_condbatch_salvgut_tables-", ver, ".xlsx")))## Error in combine_de_tables(g_isc_new_condbatch, keepers = salv_gut, excel = paste0("excel/g_isc_new_condbatch_salvgut_tables-", : object 'g_isc_new_condbatch' not foundg_pvalue_salvgut_sig <- extract_significant_genes(g_salvgut, fc=0.01,
excel=paste0("excel/g_isc_new_condbatch_psig_salvgut-", ver, ".xlsx"))## Error in extract_significant_genes(g_salvgut, fc = 0.01, excel = paste0("excel/g_isc_new_condbatch_psig_salvgut-", : object 'g_salvgut' not foundg_salvgut_sig <- extract_significant_genes(g_salvgut,
excel=paste0("excel/g_isc_new_condbatch_sig_salvgut-", ver, ".xlsx"))## Error in extract_significant_genes(g_salvgut, excel = paste0("excel/g_isc_new_condbatch_sig_salvgut-", : object 'g_salvgut' not foundg_pvalue_infuninf_sig <- extract_significant_genes(g_infuninf, fc=0.01,
excel=paste0("excel/g_isc_new_condbatch_psig_infuninf-", ver, ".xlsx"))## Error in extract_significant_genes(g_infuninf, fc = 0.01, excel = paste0("excel/g_isc_new_condbatch_psig_infuninf-", : object 'g_infuninf' not foundg_infuninf_sig <- extract_significant_genes(g_infuninf,
excel=paste0("excel/g_isc_new_condbatch_sig_infuninf-", ver, ".xlsx"))## Error in extract_significant_genes(g_infuninf, excel = paste0("excel/g_isc_new_condbatch_sig_infuninf-", : object 'g_infuninf' not found##h_infuninf_sig <- extract_significant_genes(h_infuninf, excel=FALSE)
##h_salvgut_sig <- extract_significant_genes(h_salvgut, excel=FALSE)
##i_infuninf_sig <- extract_significant_genes(i_infuninf, excel=FALSE)
##i_salvgut_sig <- extract_significant_genes(i_salvgut, excel=FALSE)isc_desva <- sm(all_pairwise(isc_most, model_batch="sva"))
contrasts_performed <- isc_desva$edger$contrasts$names
contrasts_performedtmp <- sm(saveme(filename=this_save))## Error in paste0(getwd(), "/", directory, "/", filename): object 'this_save' not found