Merge branch 'master' into bars_update

R/deseq2_fun.R

@@ -134,25 +134,26 @@ deseq2_fun <- function(data = data, output = "./deseq/", column1 = "", verbose =
     geoMeans = apply(DESeq2::counts(dseq), 1, gm_mean)
     dseq2 = estimateSizeFactors(dseq, geoMeans = geoMeans)
 
-    flog.info('DESeq2...')
-    print(dseq2)
+    # flog.info('DESeq2...')
+    # print(dseq2)
 
     dseq3 = DESeq2::DESeq(dseq2, test="Wald", fitType="parametric")
     flog.debug(show(dseq3))
 
-    res = results(dseq3, cooksCutoff = FALSE)
+    res = results(dseq3, cooksCutoff = FALSE, contrast = c(column1,combinaisons[1,col] , combinaisons[2,col]))
     flog.debug(show(res))
-    alpha = 0.05
 
     # outlist1 <- list()
 
+    flog.info('Plot...')
+    alpha = 0.05
     if(length(which(res$padj < alpha)) > 0){
-      # sigtab = res[which(res$padj < alpha), ]
-      sigtab = res
-      sigtab = cbind(row.names(sigtab),as(sigtab, "data.frame"), as(tax_table(data)[rownames(sigtab), ], "matrix"))
-      colnames(sigtab)[1]=resultsNames(dseq3)[2]
+      sigtab = res[which(res$padj < alpha), ]
+      # sigtab = res
+      tabOUT = cbind(taxon_id = row.names(res),as(res, "data.frame"), as(tax_table(data)[rownames(res), ], "matrix"))
+      colnames(res)[1]=resultsNames(dseq3)[2]
       # save.image("debug.rdata")
-      write.table(sigtab, file = paste(output,'/signtab_',column1,'_',paste(combinaisons[,col],collapse="_vs_"),'.csv',sep=''),quote=FALSE,sep="\t", row.names=FALSE)
+      write.table(tabOUT, file = paste(output,'/signtab_',column1,'_',paste(combinaisons[,col],collapse="_vs_"),'.csv',sep=''),quote=FALSE,sep="\t", row.names=FALSE)
 
       if(rank != 'ASV'){
         fun <- paste('x = tapply(sigtab$log2FoldChange, sigtab$',rank,', function(x) max(x))',sep='')
@@ -174,7 +175,7 @@ deseq2_fun <- function(data = data, output = "./deseq/", column1 = "", verbose =
       Ftable = sigtab[,c("baseMean","log2FoldChange","stat","pvalue","padj",rank)]
       ggtable <- ggtexttable(Ftable,theme = ttheme("mOrange"),rows=NULL)
 
-      pdf(file=paste(output,'/deseq2_',column1,'.pdf',sep=''),width=15,height=16)
+      pdf(file=paste(output,'/deseq2_',column1,"_", paste(combinaisons[,col],collapse="_vs_"), '.pdf',sep=''),width=15,height=16)
       grid.arrange(p,ggtable,top=text_grob(paste('Combination ',combinaisons[1,col], ' VS ' , combinaisons[2,col],sep=''), size=20))
       invisible(dev.off())
 

R/diversity_beta_light.R

@@ -10,6 +10,7 @@
 #' @param ord0 Currently supported method options are: c("DCA", "CCA", "RDA", "CAP", "DPCoA", "NMDS", "MDS", "PCoA")
 #' @param output The output file directory.
 #' @param tests Whether to compute tests or not (TRUE/FALSE)
+#' @param axes Axes to plot (c(1,2))
 #' @param verbose Verbose level. (1: quiet, 2: print infos, 3: print infos + debug)
 #'
 #' @return Return specific plots and tests in list and output them in the output directory.
@@ -25,7 +26,7 @@
 
 # Decontam Function
 
-diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, dist0 = "bray", ord0 = "MDS", output="./plot_div_beta/", tests = TRUE, verbose = 2) {
+diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, dist0 = "bray", ord0 = "MDS", output="./plot_div_beta/", axes = c(1,2), tests = TRUE, verbose = 2) {
 
   if(verbose == 3){
   invisible(flog.threshold(DEBUG))
@@ -69,10 +70,10 @@ diversity_beta_light <- function(psobj, rank = "ASV", col = NULL, cov = NULL, di
   flog.info('Plot ...')
   resBeta <- list()
   if(!is.null(cov)){
-  p1 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = col, shape = cov1[length(cov1)] ) +
+  p1 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = col, shape = cov1[length(cov1)], axes = axes ) +
   theme_bw() + ggtitle(glue::glue("{ord0} + {dist0}")) + stat_ellipse() + scale_shape_manual(values = 0:10)
 }else{
-  p1 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = col) +
+  p1 <- plot_samples(data_rank, ordinate(data_rank, ord0, dist0), color = col, axes = axes ) +
   theme_bw() + ggtitle(glue::glue("{ord0} + {dist0}")) + stat_ellipse()
 }
   # plot(p1)