Hi,
I would like to conduct DE analysis of miRNA and mRNA using DESeq and
EdgeR on two conditions (Breast cancer subtypes) the problem is that
for one condition I have 122 samples and for the second only 22. I
would like to know if it is O.K to run DE on such different size
groups ?
What I tried to do is to run 100 different permutations of 22 samples
out of 122 and to try to run DE and search for differentially
expressed miRNA in all 100 different permutations against the 22 from
the second condition.
I got only one miRNA that is differentially expressed in DESeq in all
permutaions but when I run 122 samples against 22 samples I got no
such miRNA. There is a difference between EdgeR results as well.
Is my way of creating samller groups is applicable? Or is there any
other way to deal with such different group sizes?
Thanks!
-- output of sessionInfo():
R version 2.15.1 (2012-06-22)
Platform: x86_64-pc-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=C LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] edgeR_2.6.7 limma_3.12.1 DESeq_1.8.3 locfit_1.5-8
Biobase_2.14.0
loaded via a namespace (and not attached):
[1] annotate_1.34.0 AnnotationDbi_1.18.1 BiocGenerics_0.2.0
[4] DBI_0.2-5 genefilter_1.38.0 geneplotter_1.34.0
[7] grid_2.15.1 IRanges_1.14.3 lattice_0.20-6
[10] RColorBrewer_1.0-5 RSQLite_0.11.1 splines_2.15.1
[13] stats4_2.15.1 survival_2.36-14 xtable_1.7-0
>
--
Sent via the guest posting facility at bioconductor.org.
> Date: Tue, 3 Jul 2012 03:08:25 -0700 (PDT)
> From: "Moriah [guest]" <guest at="" bioconductor.org="">
> To: bioconductor at r-project.org, moriahcohen at gmail.com
> Subject: [BioC] Very Different group sizes in DE of two conditions
>
> Hi,
>
> I would like to conduct DE analysis of miRNA and mRNA using DESeq
and
> EdgeR on two conditions (Breast cancer subtypes) the problem is that
for
> one condition I have 122 samples and for the second only 22. I
would
> like to know if it is O.K to run DE on such different size groups ?
Yes, it is no problem whatsoever.
Gordon
> What I tried to do is to run 100 different permutations of 22
samples
> out of 122 and to try to run DE and search for differentially
expressed
> miRNA in all 100 different permutations against the 22 from the
second
> condition.
>
> I got only one miRNA that is differentially expressed in DESeq in
all
> permutaions but when I run 122 samples against 22 samples I got no
such
> miRNA. There is a difference between EdgeR results as well.
>
> Is my way of creating samller groups is applicable? Or is there any
> other way to deal with such different group sizes?
>
> Thanks!
>
> -- output of sessionInfo():
>
> R version 2.15.1 (2012-06-22)
> Platform: x86_64-pc-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=C LC_NAME=C
> [9] LC_ADDRESS=C LC_TELEPHONE=C
> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] edgeR_2.6.7 limma_3.12.1 DESeq_1.8.3 locfit_1.5-8
Biobase_2.14.0
>
> loaded via a namespace (and not attached):
> [1] annotate_1.34.0 AnnotationDbi_1.18.1 BiocGenerics_0.2.0
> [4] DBI_0.2-5 genefilter_1.38.0 geneplotter_1.34.0
> [7] grid_2.15.1 IRanges_1.14.3 lattice_0.20-6
> [10] RColorBrewer_1.0-5 RSQLite_0.11.1 splines_2.15.1
> [13] stats4_2.15.1 survival_2.36-14 xtable_1.7-0
>>
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