[BioC] limma: cannot repoduce older analysis

Wolfgang Huber huber at ebi.ac.uk
Thu Jul 24 12:41:58 CEST 2008

Hi Philipp

the quickest way to figure out what's going on may be to download and
install an older version of R (as good as you can remember what it was),
and then your script and see exactly at what point your results start to

Is "targets" the same? (esp if you imported it from text file via
read.table or the like, there can be surprises e.g. to do with
locales/encoding, special characters...)

Best wishes

Wolfgang Huber  EBI/EMBL  Cambridge UK  http://www.ebi.ac.uk/huber

24/07/2008 11:23 Philipp Pagel scripsit
> 	Dear list,
> About 3 months ago I analyzed a simple two-color array experiment and got
> results that looked quite reasonable and biologically sound. For some reason I
> wanted to repeat the analysis and add a few plots that I had not included
> before.
> When I got VERY different results in my toptable, I assumed I must have
> changed something in my approach so I simply ran my original analysis
> script again and found I was unable to reproduce the original toptable.
> I have spent quite some time trying to debug the problem and have to say
> that I am stuck. I have the original data files and the original
> R-script. The normalization is 100% reproducible - i.e. the normalized
> MALists seem to be identical. Yet when searching for differential
> expression I get totally different results.
> The only difference between the two runs lies in updates to R and limma in
> the meantime. Unfortunately, I did not record which version of R, limma etc. I
> had used, originally. My current environment is this:
> 	> sessionInfo()
> 	R version 2.7.1 (2008-06-23)
> 	x86_64-pc-linux-gnu
> 	locale:
> 	attached base packages:
> 	[1] splines   stats     graphics  utils     datasets  grDevices methods   base
> 	other attached packages:
> 	[1] statmod_1.3.6   MASS_7.2-42     xtable_1.5-2    limma_2.14.2    lattice_0.17-10
> 	[6] cairoDevice_2.8
> 	loaded via a namespace (and not attached):
> 	[1] grid_2.7.1  tools_2.7.1
> My search for differential expression seems pretty standard to me:
> 	MA$design <- modelMatrix(targets, ref="control")
> 	# flag out controls etc.
> 	MA$weights[MA$genes$Status != 'miRNA', ] = 0.0
> 	# sort spots by ID to put replicates next to each other
> 	MA2 <- MA[order(MA$genes$ID), ]
> 	dupfit <- duplicateCorrelation(MA2, ndups=4)
> 	fit <- lmFit(MA2, ndups=4, correlation=dupfit$consensus)
> 	fit <- eBayes(fit)
> 	tt <- topTable(fit, number=100)
> I have siftet through the changelog of limma hoping to find a hint about
> some changed default or behaviour in lmFit or eBayes but saw nothing
> that seemed to expain my problem.
> Any hints apprechiated.
> cu
> 	Philipp

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