Hi Mike,

Thanks for your reply; my interest would be in the genes that are
differentially expressed in the resistant cells versus the sensitive cells
but also using the control samples to identify any differentially expressed
genes which changing as a result of a "non-specific" effect of treatment
with the drug.

Best,
Dave


On 15 June 2014 16:19, Michael Love <michaelisaiahlove@gmail.com> wrote:

> hi Dave,
>
> On Sun, Jun 15, 2014 at 8:46 AM, Dave Wettmann [guest]
> <guest@bioconductor.org> wrote:
> > 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.
>
> Maybe you can say more about what specific evidence of differential
> expression you are looking for. It sounds like you might have
> something in mind more than those genes which are differently
> expressed in the resistant group compared to the sensitive group.
>
> Note you can contrast any pair of the three levels using the contrast
> argument. See section 3.2 of the vignette.
>
> Mike
>
> > 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
> >
> >
> > --
> > Sent via the guest posting facility at bioconductor.org.
> >
> > _______________________________________________
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