I've posted that question on a different board, just in case it would have more exposure here, here is what I'm struggling with DESeq2. I'm experiencing issues with the replicates of our experiment. We should be comparing 3 types of treatments in one heatmap.
- Ctrl vs T
- Ctrl vs B
- Ctrl vs A
Each of which have 3 replicates. The following code works very well when I don't use replicates, and simply compare one treatment vs control. Also, when calling mcols, it should show the 3 comparisons we will use in our heatmap, though it only says CTRL vs T (if I don't use replicates) or T vs A in this case.
So here are my two questions:
- Is there a better way to define samples$condition?
- How should I use mcols to have the 3 comparisons?
Thanks (ps: I'm not an R expert)
# DESeq1 libraries
library( "DESeq2" ) library("Biobase") # Heatmap libraries library(RColorBrewer) library( "genefilter" ) library(gplots) # Start loading matrix data clba = read.table("matrix_duplicates_merged_CLBA.txt", header=TRUE, row.names=1) head(clba) samplesclba <- data.frame(row.names=c("C1", "C2", "C3", "T1", "T2", "T3", "B1", "B2", "B3", "A1", "A2", "A3"), condition=as.factor(c(rep("C",3), rep("T", 3), rep("B", 3), rep("A", 3)))) ## Relevel doesn't work with replicates samples$condition <- relevel(samples$condition, "C") Error in samples$condition : object of type 'closure' is not subsettable
Then here is the second part of the code, where I'm experiencing issues with the dataframe and mcols. I'm not defining data.frame very well, and I've explored results and coef() function unsuccessfully.
# Launch DESeq2
ddsclba <- DESeqDataSetFromMatrix(countData = as.matrix(clba), colData=samplesclba, design=~condition) ddsclba <- DESeq(ddsclba, betaPrior=FALSE)
At this point, when I don't use replicate with samples$condition, I have a clear comparison of Control vs Treatment T. But it's unclear if Control vs. B and Control vs. A are happening in the log calculation. Here since I use replicates, I can't relevel to Control, though even if I did, it wouldn't show the 3 comparisons I'm looking to have, ie, C vs. T, C vs. B and C vs. A.
# Results resclba <- results( ddsclba ) mcols(resclba, use.names=TRUE) DataFrame with 6 rows and 2 columns type description <character> <character> baseMean intermediate the base mean over all rows log2FoldChange results log2 fold change: condition T vs A lfcSE results standard error: condition T vs A stat results Wald statistic: condition T vs A pvalue results Wald test p-value: condition T vs A padj results BH adjusted p-values # Heatmap with top 35 genes rldclba <- rlogTransformation(ddsclba) topVarGenesclba <- order( rowVars( assay(rldclba) ), decreasing=TRUE ) [1:35] hmcol <- colorRampPalette( rev(brewer.pal(9, "RdBu")))(255) heatmap.2( assay(rldclba)[ topVarGenesclba, ], Colv=FALSE, scale="row", trace="none", dendrogram="row", col = hmcol