Entering edit mode
Al Ivens
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270
@al-ivens-1646
Last seen 10.2 years ago
Hi all,
I am doing some analyses of Affy arrays using limma. Following the
manual, I generated the fit2 object using the default eBayes settings,
and topTable with (almost) default settings.
> dim(eset)
Features Samples
22625 15
> fit <- lmFit(eset,designMATRIX)
> fit2 <- eBayes(contrasts.fit(fit,contrast.matrix))
> TT <- topTable(fit2,adjust.method="BH",number=length(fit2$genes))
I am now using decideTests, and have read the help that goes with it.
However, I still can't decide (no pun intended) on what is the best
method ("separate", "global", "hierarchical", "nestedF") to apply with
what adjust.method ("none", "BH", "fdr", "BY", "holm"). I have so far
left adjust.method as "BH", and varied the method. I can chose one
(global) that gives me most of the genes I "want", but I'd rather
chose
the method more objectively. I have 5 contrasts, so am guessing from
the email archives that nestedF is probably not appropriate for so few
contrasts?
Are there any general guidelines as to which is the best method to use
when?
Thanks in anticipation,
a
> sessionInfo()
R version 2.6.0 (2007-10-03)
i386-pc-mingw32
locale:
LC_COLLATE=English_United Kingdom.1252;LC_CTYPE=English_United
Kingdom.1252;LC_MONETARY=English_United
Kingdom.1252;LC_NUMERIC=C;LC_TIME=English_United Kingdom.1252
attached base packages:
[1] grid splines tools stats graphics grDevices utils
datasets methods base
other attached packages:
[1] statmod_1.3.1 celeganscdf_2.0.0
arrayQualityMetrics_1.2.0 latticeExtra_0.3-1 CCl4_1.0.6
[6] simpleaffy_2.14.05 affyPLM_1.14.0 gcrma_2.10.0
matchprobes_1.10.0 RColorBrewer_1.0-2
[11] vsn_3.2.1 genefilter_1.16.0 survival_2.34
geneplotter_1.16.0 lattice_0.17-2
[16] annotate_1.16.1 xtable_1.5-2
AnnotationDbi_1.0.6 RSQLite_0.6-4 DBI_0.2-4
[21] celegans_2.0.1 affy_1.16.0
preprocessCore_1.0.0 affyio_1.6.1 Biobase_1.16.1
[26] limma_2.12.0
loaded via a namespace (and not attached):
[1] KernSmooth_2.22-21
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