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Paul Boutros
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340

@paul-boutros-371
Last seen 8.3 years ago

Hello,
I'm having some troubles interpreting how/why siggenes performed a
certain
number of permutations on my dataset. This is an affy dataset that
was
normalized by:
data <- ReadAffy(filenames=cel.files, phenoData="phenodata.txt");
eset <- expresso(data, normalize.method="constant",
bgcorrect.method="none",
pmcorrect.method="mas", summary.method="avgdiff");
I realize that the normalization is a bit unusual: this study is
actually
testing a range of normalization methods. This is a two-class
experiment with
3 arrays in each group:
> eset;
Expression Set (exprSet) with
22690 genes
6 samples
phenoData object with 1 variables and 6 cases
varLabels
Group: read from file
> design;
[1] 1 1 0 1 0 0
So to do a SAM-like analysis I used:
SAM.data <- sam(data=eset, cl=design, var.equal=FALSE, B=1000);
And I expected there to be 6! = 720 total possible permutations. So I
was
surprised to get this output:
> SAM.data <- sam(data=eset, cl=design, var.equal=FALSE, B=1000);
We're doing 20 complete permutations
Why does siggenes think there are only 20 complete permutations to be
used?
Have I done something wrong, or is my understanding of how the
permutations are
done in error?
This is R 2.2.1 and siggenes 1.4.0 on WinXP.
Paul