X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=rsem-find-DE;h=98db6d8b91e141f148f3274fd305da107e182bb5;hb=1d786dca8b4c9c1e2176a28a669d2d16cd93e395;hp=e9d25f7d38d957f2dbfc2e9a92762d16468d200f;hpb=8ca5b7c2fb57bc523431c1e37d5ab9337eccbc37;p=rsem.git

diff --git a/rsem-find-DE b/rsem-find-DE
index e9d25f7..98db6d8 100755
--- a/rsem-find-DE
+++ b/rsem-find-DE
@@ -1,14 +1,14 @@
 #!/usr/bin/env Rscript
 
 printUsage <- function() {
-  cat("Usage: rsem-find-DE data_matrix_file [--ngvector ngvector_file] number_sample_condition1 FDR_rate output_file\n\n")
+  cat("Usage: rsem-find-DE data_matrix_file [--ngvector ngvector_file] number_of_samples_in_condition_1 FDR_rate output_file\n\n")
   cat("This script calls EBSeq to find differentially expressed genes/transcripts in two conditions.\n\n") 
   cat("data_matrix_file: m by n matrix containing expected counts, m is the number of transcripts/genes, n is the number of total samples.\n")
   cat("[--ngvector ngvector_file]: optional field. 'ngvector_file' is calculated by 'rsem-generate-ngvector'. Having this field is recommended for transcript data.\n")
-  cat("number_sample_condition1: the number of samples in condition 1. A condition's samples must be adjacent. The left group of samples are defined as condition 1.\n")
+  cat("number_of_samples_in_condition_1: the number of samples in condition 1. A condition's samples must be adjacent. The left group of samples are defined as condition 1.\n")
   cat("FDR_rate: false discovery rate.\n")
-  cat("output_file: the output file.\n\n")
-  cat("The results are written as a matrix with row and column names. The row names are the differentially expressed transcripts'/genes' ids. The column names are 'PPEE', 'PPDE', 'PostFC' and 'RealFC'.\n\n")
+  cat("output_file: the output file. Three files will be generated: 'output_file', 'output_file.hard_threshold' and 'output_file.all'. The first file reports all DE genes/transcripts using a soft threshold (calculated by crit_func in EBSeq). The second file reports all DE genes/transcripts using a hard threshold (only report if PPEE <= fdr). The third file reports all genes/transcripts. The first file is recommended to be used as DE results because it generally contains more called genes/transcripts.\n\n")
+  cat("The results are written as a matrix with row and column names. The row names are the genes'/transcripts' ids. The column names are 'PPEE', 'PPDE', 'PostFC' and 'RealFC'.\n\n")
   cat("PPEE: posterior probability of being equally expressed.\n")
   cat("PPDE: posterior probability of being differentially expressed.\n")
   cat("PostFC: posterior fold change (condition 1 over condition2).\n")
@@ -58,12 +58,26 @@ if (is.null(ngvector)) {
 }
 stopifnot(!is.null(EBOut))
 
-PP <- GetPPMat(EBOut)
+PP <- as.data.frame(GetPPMat(EBOut))
+fc_res <- PostFC(EBOut)
+
+# soft threshold, default output
 thre <- crit_fun(PP[, "PPEE"], fdr)
 DEfound <- rownames(PP)[which(PP[, "PPDE"] >= thre)]
 
-fc_res <- PostFC(EBOut)
-
-results <- cbind(PP[DEfound, ], fc_res$GenePostFC[DEfound], fc_res$GeneRealFC[DEfound])
+results <- cbind(PP[DEfound, ], fc_res$PostFC[DEfound], fc_res$RealFC[DEfound])
 colnames(results) <- c("PPEE", "PPDE", "PostFC", "RealFC")
 write.table(results, file = output_file)
+
+# hard threshold
+thre <- 1.0 - fdr
+DEfound <- rownames(PP)[which(PP[, "PPDE"] >= thre)]
+
+results <- cbind(PP[DEfound, ], fc_res$PostFC[DEfound], fc_res$RealFC[DEfound])
+colnames(results) <- c("PPEE", "PPDE", "PostFC", "RealFC")
+write.table(results, file = paste(output_file, ".hard_threshold", sep = ""))
+
+# all
+results <- cbind(PP, fc_res$PostFC, fc_res$RealFC)
+colnames(results) <- c("PPEE", "PPDE", "PostFC", "RealFC")
+write.table(results, file = paste(output_file, ".all", sep = ""))