microarray and t.test
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@roth-richard-1424
Last seen 10.2 years ago
Hi, I have a data matrix of gene expression data from two groups that I would like to compare using the t-test. The data has been processed using RMA and transformed using log2. I would like to compare the two groups for each gene (N=10,000 genes) and have a result that lists the p-value (at minimum) for each test, possibly in another matrix. Can anyone help me with the t.test setup for this analysis? Thanks, Rich Rich Roth, PhD Senior Scientist Molecular Medicine Neurocrine Biosciences 858-617-7204 Rich Roth, PhD Senior Scientist, Bioinformatics Molecular Medicine Neurocrine Biosciences 858-617-7204 -------------- next part -------------- "MMS <neurocrine.com>" made the following annotations on 03/06/2006 10:24:07 AM ---------------------------------------------------------------------- -------- This email may contain confidential and privileged material ...{{dropped}}
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@sean-davis-490
Last seen 3 months ago
United States
On 3/6/06 1:23 PM, "Roth, Richard" <rroth at="" neurocrine.com=""> wrote: > Hi, I have a data matrix of gene expression data from two groups that I would > like to compare using the t-test. The data has been processed using RMA and > transformed using log2. I would like to compare the two groups for each gene > (N=10,000 genes) and have a result that lists the p-value (at minimum) for > each test, possibly in another matrix. Can anyone help me with the t.test > setup for this analysis? Look at the multtest to do what you are asking. However, there are more powerful tests for microarrays included in the siggenes and limma packages, as well as several others. Each has a vignette or other documentation to get you going. Limma has a complete user guide that includes and example of affy data in two classes, if I recall correctly. Sean
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@hassane-duane-1639
Last seen 10.2 years ago
Rich, I've sometimes suggested the mt.wrapper function which will get you exactly what you want quickly (from the webbioc package by Colin Smith). As a wrapper, it integrates the functionality in multtest. That said, you will be better off in the long term to look at multtest itself and the other more powerful packages that Sean mentioned. Best, Duane -----Original Message----- From: Roth, Richard [mailto:rroth@neurocrine.com] Sent: Monday, March 06, 2006 1:24 PM To: bioconductor at stat.math.ethz.ch Subject: [BioC] microarray and t.test Hi, I have a data matrix of gene expression data from two groups that I would like to compare using the t-test. The data has been processed using RMA and transformed using log2. I would like to compare the two groups for each gene (N=10,000 genes) and have a result that lists the p-value (at minimum) for each test, possibly in another matrix. Can anyone help me with the t.test setup for this analysis? Thanks, Rich Rich Roth, PhD Senior Scientist Molecular Medicine Neurocrine Biosciences 858-617-7204 Rich Roth, PhD Senior Scientist, Bioinformatics Molecular Medicine Neurocrine Biosciences 858-617-7204
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