Hi,
I am trying to analyze RNA-Seq Data with DESeq2 and could use some help.
I have 2 genotypes and 14 timepoints. I want to find differences in gene
expression between both genotypes overall and at every timepoint and
between every two timepoints in each genotype.
Here is what I did so far.
library("DESeq2")
directory<-"............."
sampleFiles <- grep("??",list.files(directory),value=TRUE)
time <- factor(c("T12", "T13", "T14", "T1", "T11", "T5", "T7", "T2",
"T9", "T3", "T6", "T8", "T4", "T10", "T12", "T13", "T14", "T1", "T11",
"T5", "T7", "T2", "T9", "T3", "T6", "T8", "T4", "T10" ))
genotype <-
factor(c("GF","GF","GF","GF","GF","GF","GF","GF","GF","GF","GF","GF","GF","GF","VB","VB","VB","VB","VB","VB","VB","VB","VB","VB","VB","VB","VB","VB"))
sampleTable<-data.frame(sampleName=sampleFiles, fileName=sampleFiles,
genotype=genotype, time=time)
ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable=sampleTable,
directory=directory, design=~genotype+time+time:genotype)
ddsHTSeq$genotype<-factor(ddsHTSeq$genotype, levels=c("GF","VB"))
ddsHTSeq$time <- factor(ddsHTSeq$time, levels=c("T1", "T2", "T3", "T4",
"T5", "T6", "T7", "T8", "T9", "T10", "T11", "T12", "T13", "T14"))
dds <- DESeq(ddsHTSeq)
res <- results(dds)
ddsHTSeq <- estimateSizeFactors(ddsHTSeq)
ddsHTSeq <- estimateDispersions(ddsHTSeq)
ddsLRT <- nbinomLRT(dds, reduced = formula(~time+genotype))
or ~genotype + time in the full and ~time in the reduced formula, but I
think this is not suitable for my experiment. When I use the first
design and do plotMA, I have no significant genes at all, so I must be
doing something wrong. I would be greatfull for some help. Thank you.
> sessionInfo()
R version 3.1.1 (2014-07-10)
Platform: x86_64-redhat-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] DESeq2_1.4.5 RcppArmadillo_0.4.450.1.0
[3] Rcpp_0.11.2 GenomicRanges_1.16.4
[5] GenomeInfoDb_1.0.2 IRanges_1.22.10
[7] BiocGenerics_0.10.0
loaded via a namespace (and not attached):
[1] annotate_1.42.1 AnnotationDbi_1.22.6 Biobase_2.20.1
[4] DBI_0.2-5 genefilter_1.46.1 geneplotter_1.42.0
[7] grid_3.1.1 lattice_0.20-29 locfit_1.5-9.1
[10] RColorBrewer_1.0-5 RSQLite_0.11.2 splines_3.1.1
[13] stats4_3.1.1 survival_2.37-7 XML_3.98-1.1
[16] xtable_1.7-1 XVector_0.4.0
--
Nadia Kamal
Bielefeld University
Center for Biotechnology (Cebitec)
Genome Research
Universitätsstraße 27
33615 Bielefeld
Germany
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