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

@@ -129,6 +129,7 @@ load the data:
 
 then do the plotting :)
 
+```
 library(ggplot2)
 library(reshape2)
 library(RColorBrewer)
@@ -150,7 +151,7 @@ then do the plotting :)
 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$variable)
+seqtab.m$variable <- as.character(seqtab.m$variable
 seqtab.m$Domain <- sapply(strsplit(seqtab.m$variable, "-"), "[[", 1)
 seqtab.m$Phylum <- sapply(strsplit(seqtab.m$variable, "-"), "[[", 2)
 seqtab.m$Class <- sapply(strsplit(seqtab.m$variable, "-"), "[[", 3)
@@ -169,6 +170,7 @@ then do the plotting :)
   theme(text=element_text(family="Serif", size=16)) +
   theme(axis.text.x=element_text(angle=45, hjust=1))
 }
+```
 
 So the bit above creates the function called `plotTaxon()`, which we can then use to generate the plots.