Meta-analyses of data from two (or more) microarray data sets.

Jeremy Miller

Email Addresses
General questions: jeremyinla@gmail.com
WGCNA questions: shorvath@mednet.ucla.edu

ABSTRACT

Given the large number of microarray analyses (sometimes of similar design) one question that may arise is "if group A and group B both ran microarray studies and reported some results, how compatible are these results?" There are currently no standard methods for comparing results from multiple microarray data sets, but that does not mean that it can't be done; for example, some methods can be found at the WGCNA website. This tutorial describes a step by step example of how one can compare two data sets, whether or not these studies were performed using the same microarray platforms.

Files for Tutorial:

Tutorial with embedded R-code

Tutorial document (.doc): contains word version (recommended for MAC--images may not display on a PC).

Tutorial document (.pdf): contains pdf version (recommended for PC).

Files required for running meta-analysis

Other required files (.zip): format of data explained in code documents

Other material regarding weighted gene co-expression network analysis

Weighted Gene Co-Expression Network Page

The weighted gene co-expression network analysis method is described in Theory Paper 1: Zhang and Horvath (2005)

For a more mathematical description of weighted gene co-expression networks, see: Dong and Horvath (2007, 2008)

Reference

This tutorial is a condensed version of the analysis performed in "Miller JA, Horvath S, Geschwind DH. (2010) Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways. Proc Natl Acad Sci U S A. 2010 Jul 13;107(28):12698-703."

2011-04-14

Please send your suggestions and comments to: shorvath@mednet.ucla.edu