Hello, 

I'm trying to analyse an RNA-seq dataset where I have three treatment levels, "early", "late", and "untreated". I would like to know how to do a nested comparison in DESeq2 such that I compare ((early Vs untreated) Vs (late Vs untreated)).

I've pasted my code below:

samples = read.csv("samples.csv",header=TRUE)

#start edgeR, which you will use to collapse replicates and make the count matrix
library("edgeR")

#proceed to read in count data from .count files, collapse replicates, write count matrix
counts = readDGE(samples$countf)$counts
colnames(counts) = samples$shortname
d = DGEList(counts=counts, group=colnames(counts))

#attach the column data to from the sample sheet to the variable coldata
coldata = with(samples,data.frame(shortname = I(shortname), condition = condition))

#attach the count data to the variable countdata
countdata = counts

#start DESeq2
library("DESeq2")

#construct your DESeq2 data set, making sure to specify the design matrix here
dds <- DESeqDataSetFromMatrix(countData = countdata,
colData = coldata,
design = ~ condition)

#relevel controls
dds$condition <- relevel(dds$condition, "uninfected")

#run DESeq2 on the dataset
dds <- DESeq(dds)

#print out results names
resultsNames(dds)

#get the following:
 [1] "Intercept"             "conditionuninfected" "conditionearly"                
 [4] "conditionlate"    

#input contrast formula to get results
resdds <- results(dds, contrast = list(c( c("conditionearly", "conditionuninfected")),(c("conditionlate","conditionuninfected"))))

#get the following error
Error in cleanContrast(object, contrast, expanded = isExpanded, listValues = listValues,  : 
  elements in the contrast list should only appear in the numerator (first element of contrast list)
or the denominator (second element of contrast list), but not both

What is the correct contrast formula to use here?

Erin

Results of sessionInfo():

R version 3.1.3 (2015-03-09)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.2 LTS

locale:
 [1] LC_CTYPE=en_CA.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_CA.UTF-8        LC_COLLATE=en_CA.UTF-8    
 [5] LC_MONETARY=en_CA.UTF-8    LC_MESSAGES=en_CA.UTF-8   
 [7] LC_PAPER=en_CA.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] DESeq2_1.6.3              RcppArmadillo_0.4.650.1.1
 [3] Rcpp_0.11.5               GenomicRanges_1.18.4     
 [5] GenomeInfoDb_1.2.4        IRanges_2.0.1            
 [7] S4Vectors_0.4.0           BiocGenerics_0.12.1      
 [9] edgeR_3.8.6               limma_3.22.7             

loaded via a namespace (and not attached):
 [1] acepack_1.3-3.3      annotate_1.44.0      AnnotationDbi_1.28.2
 [4] base64enc_0.1-2      BatchJobs_1.6        BBmisc_1.9          
 [7] Biobase_2.26.0       BiocParallel_1.0.3   brew_1.0-6          
[10] checkmate_1.5.2      cluster_2.0.1        codetools_0.2-11    
[13] colorspace_1.2-6     DBI_0.3.1            digest_0.6.8        
[16] fail_1.2             foreach_1.4.2        foreign_0.8-63      
[19] Formula_1.2-0        genefilter_1.48.1    geneplotter_1.44.0  
[22] ggplot2_1.0.1        grid_3.1.3           gtable_0.1.2        
[25] Hmisc_3.15-0         iterators_1.0.7      lattice_0.20-31     
[28] latticeExtra_0.6-26  locfit_1.5-9.1       MASS_7.3-40         
[31] munsell_0.4.2        nnet_7.3-9           plyr_1.8.1          
[34] proto_0.3-10         RColorBrewer_1.1-2   reshape2_1.4.1      
[37] rpart_4.1-9          RSQLite_1.0.0        scales_0.2.4        
[40] sendmailR_1.2-1      splines_3.1.3        stringr_0.6.2       
[43] survival_2.38-1      tools_3.1.3          XML_3.98-1.1        
[46] xtable_1.7-4         XVector_0.6.0 

Note that ((early Vs untreated) Vs (late Vs untreated)) is equivalent to just (early Vs late) because the "untreated" terms cancel each other out. In algebraic terms, you're simplifying (X - C) - (Y - C) to (X - Y).