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Katarzyna Bryc
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10
@katarzyna-bryc-1808
Last seen 10.2 years ago
Dear List,
I have a question on correctly modeling a situtation to find
significantly differentiated genes with Limma. I have Affy arrays for
pediatric patients collected before the patients were treated with a
drug for 4 months. After this time period, some patients had a side
effect of significant weight gain, while others did not. I wish to
find
the genes which significantly differentiate patients who gained weight
with the treatment from those who did not suffer this side effect.
Since
these are pediatric patients, I also wish to control for Sex and Age
(continuous variable).
I understand that with Limma I can model the following:
Gene Expression = Age + Sex + Weight Gain
but I actually wish to look at Weight Gain as the dependent variable,
and Gene Expression as one of the independent variables (I still
control
for Age and Sex). Thus, I actually wish to model
Weight Gain = Age + Sex + Gene Expression
My questions are:
1. Will these two models give me the same results for finding genes
significant in predicting Weight Gain?
2. If not, is there a way to model this using either Limma or another
Bioconductor method?
Thank you for any helpful words,
Kasia Bryc
