Separate channel analysis on connected design
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@luis-a-alcaraz-4541
Last seen 9.6 years ago
Hi, I'm trying to analyse data from a microarray experiment which consist in three mutants compared to wild type in a connected design (the experimental design is like in a 2x2 factorial design) with limma. When I do the analysis like in a factorial design (page 45 of the manual) I get a number of differentially expressed genes considerably lower than when I do separate channel analysis (page 50). From a biological point of view, for me it makes sense the new genes that I found with separate channel analysis, but I don't know if this kind of analysis (separate channel analysis with connected design) is right from a statistical point of view. What do you think? Thanks! Luis. [[alternative HTML version deleted]]
Microarray limma Microarray limma • 746 views
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Naomi Altman ★ 6.0k
@naomi-altman-380
Last seen 3.0 years ago
United States
I prefer it. Theoretically speaking, you should get a bit more power from separate channel analysis. --Naomi At 04:53 AM 3/14/2011, Luis A. Alcaraz wrote: >Hi, > >I'm trying to analyse data from a microarray experiment which consist in >three mutants compared to wild type in a connected design (the experimental >design is like in a 2x2 factorial design) with limma. >When I do the analysis like in a factorial design (page 45 of the manual) I >get a number of differentially expressed genes considerably lower than when >I do separate channel analysis (page 50). From a biological point of view, >for me it makes sense the new genes that I found with separate channel >analysis, but I don't know if this kind of analysis (separate channel >analysis with connected design) is right from a statistical point of >view. What do you think? >Thanks! > >Luis. > > [[alternative HTML version deleted]] > >_______________________________________________ >Bioconductor mailing list >Bioconductor at r-project.org >https://stat.ethz.ch/mailman/listinfo/bioconductor >Search the archives: >http://news.gmane.org/gmane.science.biology.informatics.conductor
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Hi Naomi, Thank you very much! Just one more question... what about if I have the two design 2x2 but in two times (for example at 24h and 48h), I mean, I have two independent 2x2 designs. Can I analyse together both experiments (using separate channel) if I want to extract data for the comparison for one sample at 24h and 48h?. Thanks! Luis. On Mon, Mar 14, 2011 at 10:14 PM, Naomi Altman <naomi@stat.psu.edu> wrote: > I prefer it. Theoretically speaking, you should get a bit more power from > separate channel analysis. > > --Naomi > > > > At 04:53 AM 3/14/2011, Luis A. Alcaraz wrote: > >> Hi, >> >> I'm trying to analyse data from a microarray experiment which consist in >> three mutants compared to wild type in a connected design (the >> experimental >> design is like in a 2x2 factorial design) with limma. >> When I do the analysis like in a factorial design (page 45 of the manual) >> I >> get a number of differentially expressed genes considerably lower than >> when >> I do separate channel analysis (page 50). From a biological point of view, >> for me it makes sense the new genes that I found with separate channel >> analysis, but I don't know if this kind of analysis (separate channel >> analysis with connected design) is right from a statistical point of >> view. What do you think? >> Thanks! >> >> Luis. >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > > > [[alternative HTML version deleted]]
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