Affymetrix analysis
1
0
Entering edit mode
Christy Toms ▴ 10
@christy-toms-1325
Last seen 9.7 years ago
An embedded and charset-unspecified text was scrubbed... Name: not available Url: https://stat.ethz.ch/pipermail/bioconductor/attachments/20050701/ ce0d3c1b/attachment.pl
• 372 views
ADD COMMENT
0
Entering edit mode
Fangxin Hong ▴ 810
@fangxin-hong-912
Last seen 9.7 years ago
> Hello, > > I have a couple of questions regarding Affymetrix analysis. We have 4 >> independent experiments analysing control vs test. The experiments are >> analysing different cell types with a common phenotype with the aim of >> identifying genes associated with this phenotype. The first question is >> - is it okay to cross compare the individual experiments with each other >> even though >> they were performed independently? Independence is good. But if you use different type of cells, I don't think you can cross compare them. One possible analysis is to compare test vs control for each cell type and combine them into one analysis to identify genes that are associated with this particular phenotype, you can check out RankProd package. >> Secondly, one of the control vs test >> experiments has been performed on the Mouse Genome 430 2.0 array, whilst >> the >> remaining experiments were performed on the updated version 430A 2.0. >> So far, >> with the individual experiments we have been performing analysis using >> GCRMA on >> R, but due to the differing probe sets we can?t perform GCRMA whilst >> including >> the samples from the old chip version. Is there any possible way that >> this can >> be achieved? If your goal is to identify differentially expressed genes, you can use RankProd package which can combine data from different platforms into one study. Hope this helps Fangxin > Thanks in advance > > > Christy > > > -- > Christy Toms D.Phil > Sir William Dunn School of Pathology > Oxford OX1 3RE > 01865 285489 > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > -------------------- Fangxin Hong Ph.D. Plant Biology Laboratory The Salk Institute 10010 N. Torrey Pines Rd. La Jolla, CA 92037 E-mail: fhong at salk.edu (Phone): 858-453-4100 ext 1105
ADD COMMENT

Login before adding your answer.

Traffic: 730 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6