WeightedGeneCo-expressionNetworkAnalysis(精品).doc

Weighted Gene Co-expression Network Analysis (WGCNA) R Tutorial, Part B Module Eigengene, Survival time, and Proliferation Steve Horvath Correspondence: shorvath@, /biostat/people/horvath.htm This is part B of a self-contained R software tutorial. The first few pages are very similar to those of part A, but here we focus on studying the brown module and relating individual genes to survival outcome. Thus, the reader will be able to reproduce all of our findings. This document also serves as a tutorial to weighted gene co-expression network analysis. Some familiarity with the R software is desirable but the document is fairly self-contained. This tutorial and the data files can be found at the following webpage: /labs/horvath/CoexpressionNetwork/ASPMgene More material on weighted network analysis can be found here /labs/horvath/CoexpressionNetwork/ Contents part B (the beginning overlaps with part A) *) Weighted brain cancer network construction based on *3600* most connected genes *) Gene significance and intramodular connectivity in data sets I and II *) Module Eigengene and its relationship to individual genes *) Regressing survival time on individual gene expression and the module eigengene The data and biological implications are described in part A and in the REFERENCE for this tutorial Horvath S, Zhang B, Carlson M, Lu KV, Zhu S, Felciano RM, Laurance MF, Zhao W, Shu, Q, Lee Y, Scheck AC, Liau LM, Wu H, Geschwind DH, Febbo PG, Kornblum HI, Cloughesy TF, Nelson SF, Mischel PS (2006) Analysis of Oncogenic Signaling Networks in Glioblastoma Identifies ASPM as a Novel Molecular Target, PNAS | November 14, 2006 | vol. 103 | no. 46 | 17402-17407 Statistical References To cite the statistical methods please use Zhang B, Horvath S (2005) A General Framework for Weighted Gene Co-Expression Network Analysis. Statistical Applications in Genetics and Molecular Biology: Vol. 4: No. 1, Article 17. /sagmb/vol4/iss1/art17 Horvath S, Dong J (2008) Geometric Interpretat