Practical-3-Processing-16S-rRNA-amplicon-data.md

@@ -139,11 +139,17 @@ then do the plotting :)
   taxtable[, 5], taxtable[, 6], as.character(1:length(taxtable[, 1])), sep="-")
   seqtab <- seqtab[, grep("Chloroplast|Mitochondria", colnames(seqtab), invert=TRUE)]
   seqtab <- seqtab/rowSums(seqtab)
-      seqtab <- seqtab[, sapply(seqtab, function(x) max(x)) >= min_abund]
+  seqtab1 <- seqtab[, sapply(seqtab, function(x) max(x)) >= min_abund]
+  seqtab2 <- seqtab[, sapply(seqtab, function(x) max(x)) < min_abund]
+  colnames(seqtab2) <- paste0(colnames(seqtab2), "_Others")
+  seqtab3 <- merge(seqtab1, seqtab2, by="row.names")
+  row.names(seqtab3) <- row.names(seqtab)
+  seqtab <- seqtab3
   seqtab$sample <- rownames(seqtab)
   seqtab.m <- melt(seqtab)
   seqtab.m <- seqtab.m[grep(taxon, seqtab.m$variable),]
   seqtab.m$variable <- gsub("NA", "uncultured", seqtab.m$variable)
+  seqtab.m$variable <- gsub(".*Others", "Below_Min_Abund-Below_Min_Abund-Below_Min_Abund-Below_Min_Abund-Below_Min_Abund-Below_Min_Abund-Below_Min_Abund", seqtab.m$variable)
   seqtab.m$variable <- as.character(seqtab.m$variable)
   seqtab.m$Domain <- sapply(strsplit(seqtab.m$variable, "-"), "[[", 1)
   seqtab.m$Phylum <- sapply(strsplit(seqtab.m$variable, "-"), "[[", 2)