Hello,

I am trying to get the gene names along with the Ensembl gene ids in the final edgeR output. The problem is: I am seeing different results when I add the gene symbols and when I don't. Here is example code without gene symbols

library(edgeR)
exp2 <-read.table('exp2',header=TRUE)
y <- readDGE(exp2,labels=exp2$sample,group=exp2$treatment)
keep <- rowSums(cpm(y)>1) >= 2
y <- y[keep, , keep.lib.sizes=FALSE]
y <- calcNormFactors(y)
bcv=0.4
et_D0_D1 <- exactTest(y, pair=c("D0","D1"),dispersion=bcv^2)
write.table(topTags(et_D0_D1,n=Inf),file="test1.txt",col.names=TRUE,quote=FALSE)

Result is: ENSGACG00000003380 1.00049178363978 4.49563701685595 0.234971858102264 1

Here is the one with gene symbols added using biomart:

library(edgeR)
library(biomaRt)
exp2 <-read.table('exp2',header=TRUE)
y <- readDGE(exp2,labels=exp2$sample,group=exp2$treatment)
geneid <-rownames(y)
ga82 <-  useEnsembl(biomart="ensembl",dataset="gaculeatus_gene_ensembl",version=82)
genes <- getBM(attributes=c('ensembl_gene_id','external_gene_name'),filters='ensembl_gene_id',values=geneid,mart=ga82)
y$genes <- genes
keep <- rowSums(cpm(y)>1) >= 2
y <- y[keep, , keep.lib.sizes=FALSE]
y <- calcNormFactors(y)
bcv=0.4
et_D0_D1 <- exactTest(y, pair=c("D0","D1"),dispersion=bcv^2)
write.table(topTags(et_D0_D1,n=Inf),file="test2.txt",col.names=TRUE,quote=FALSE)

Here the result is: ENSGACG00000003380 NA -0.135739707808875 2.95905945166089 0.874200189025877 1

SessionInfo() output is given below:

R version 3.2.1 (2015-06-18)
Platform: x86_64-unknown-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

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

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

other attached packages:
[1] biomaRt_2.24.1 edgeR_3.10.4   limma_3.24.15

loaded via a namespace (and not attached):
 [1] IRanges_2.2.9        DBI_0.3.1            parallel_3.2.1
 [4] RCurl_1.95-4.7       Biobase_2.28.0       AnnotationDbi_1.30.1
 [7] RSQLite_1.0.0        S4Vectors_0.6.6      BiocGenerics_0.14.0
[10] GenomeInfoDb_1.4.3   stats4_3.2.1         bitops_1.0-6
[13] XML_3.98-1.3

I am bit puzzled. Why would addition of gene names in y$genes above change the results. Any help you could provide will be very helpful. Many thanks in advance.