[BioC] Two rma questions
naomi at stat.psu.edu
Sun Apr 18 06:03:27 CEST 2004
The strains should still be normalized together.
Normalization reduces the between array variability. If the strains are
normalized separately, the within strain variance will be falsely deflated,
increasing the apparent significance of differential expression.
If the true distribution of probe expression differs dramatically between
strains, then you are in real trouble. (I have seen this - not in strains
but in treatments that directly affect the RNA.) I am not sure what to do
- perhaps do quantile normalization using only the MM and control probes,
and then normalizing the PM probes to the quantile distribution.
The microarray analysis community has not yet addressed the problem of
normalization when there is a lot of differential expression.
At 10:42 AM 4/15/2004, Simon Kidd wrote:
>At 8.50am -0400 15/4/04, James MacDonald wrote:
>>For your first question, it is almost always preferable to run rma on
>>all samples in a set together rather than in two batches. For the second
>>question, the bug only concerns justRMA and justGCRMA, so rma and gcrma
>>are not affected.
>Thanks, however my collaborator thinks I did not phrase my question very
>well and did not emphasis enough that the genetic background of the
>strains could be very different, so this is what she thinks the question
>>We have performed two experiments. One compares fly strain A with
>>mutation M to fly strain A with a duplication for the wild type gene M.
>>The second experiment compares fly strain B with the same mutation M with
>>a different duplication for the wild type gene M. Aside from the
>>particular mutation we are assaying the genetic background of the strains
>>could be very different. If one normalizes arrays from different
>>tissues using dChip, it is suggested that the arrays get normalized
>>separately. Is this also true for RMA or should they be normalized together?
>If the strains are very different should they still be normalised together?
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Naomi S. Altman 814-865-3791 (voice)
Bioinformatics Consulting Center
Dept. of Statistics 814-863-7114 (fax)
Penn State University 814-865-1348 (Statistics)
University Park, PA 16802-2111
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