[BioC] DESeq analysis of resistance data

[Dave Wettmann [guest]]

Hello,

I am analysing RNASeq data from cancer cell lines.  I have 3 groups with n=5 in each group.  One group is sensitive to a drug, the second group has been selected for clones which have become resistant to the drug.  The third group is a control, vehicle-treated group.  I have used DESeq2 before to compare two groups but I'd be interested in advice on how to analyse these data please.  I am interested in identifying differential changes in the resistant group which might be leading to the acquired resistance.  Would analysing these data using an ANOVA model be appropriate?

Thanks,
Dave

 -- output of sessionInfo(): 

R version 3.1.0 (2014-04-10)
Platform: x86_64-unknown-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_0.4.300.0 Rcpp_0.11.1
[4] GenomicRanges_1.16.3    GenomeInfoDb_1.0.2      IRanges_1.22.7
[7] BiocGenerics_0.10.0

loaded via a namespace (and not attached):
 [1] annotate_1.42.0      AnnotationDbi_1.26.0 Biobase_2.24.0
 [4] DBI_0.2-7            genefilter_1.46.1    geneplotter_1.42.0
 [7] grid_3.1.0           lattice_0.20-29      locfit_1.5-9.1
[10] RColorBrewer_1.0-5   RSQLite_0.11.4       splines_3.1.0
[13] stats4_3.1.0         survival_2.37-7      XML_3.98-1.1
[16] xtable_1.7-3         XVector_0.4.0


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