[BioC] Differential Expression Methods

Weiwei Shi helprhelp at gmail.com
Wed Nov 22 23:05:32 CET 2006


IMHO, it is related to MAQC (microarray quality control) issue. Google
it and you can find many papers these days on this. The simple
approach you can try is using a "mild" fold change plus a t-test, as
suggested by a paper from Nature Biotech, 24, 1162-1169(2006). I tried
that approach in my own project, which does not work very well though.
You can report your result, which will be appreciated. Another
possible approach is using signal2noise, which is similar to t-test
and used in GSEA.

HTH,
weiwei

On 11/20/06, martin doherty <martin.doherty at gmail.com> wrote:
> Hi,
>
> I have Tumour and Normal technical replicates run on both FFPE and
> RNA-Later.
> These are run on X3P arrays. I am interested in comparing the outcome from
> both
> fixation methods. When I compare the transcripts classed
> as expressed in both RNA-Later and FFPE the ones found
> unique to FFPE is very small (<5%) - if I assume the RNA-Later
> samples exhibit true expression levels this is a good result.
> The intensities/background from both fixation methods is almost
> equal as well.
>
> When I look for differential expression between tumour/normal using
> both fixation methods. I find that almost half of what is differentially
> expressed in FFPE is not differentially expressed in RNA-Later. This
> disagreement would indicate that the differential expression in FFPE
> is peppered with false-positves or that RNA-Later is not picking up
> differential expression - I'd guess it is the former.
>
> The tests for differential expression was done using CyberT, SAMR and
> Muilttest,
> and a modified t-test. Does any one have any ideas what other testing
> methods would
> be worth investigating, or have any idea why there is so many false
> positives
> in FFPE?
>
>
> Thanks,
>
> Martin
>
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>
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-- 
Weiwei Shi, Ph.D
Research Scientist
GeneGO, Inc.

"Did you always know?"
"No, I did not. But I believed..."
---Matrix III



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