Package ‘ WGCNA ’
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چکیده
February 15, 2011 Version 1.00 Date 2011-02-04 Title Weighted Gene Co-Expression Network Analysis Author Peter Langfelder and Steve Horvath with contributions by Jun Dong,Jeremy Miller, Lin Song, Andy Yip, and Bin Zhang Maintainer Peter Langfelder Depends R (>= 2.3.0), stats, impute, grDevices, dynamicTreeCut (>= 1.20), utils, flashClust, qvalue, Hmisc, splines Suggests GO.db, org.Hs.eg.db, org.Mm.eg.db, AnnotationDbi, infotheo,entropy, minet ZipData no License GPL (>= 2) Description Functions necessary to perform Weighted Gene Co-Expression Network Analysis URL http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/ BranchCutting/
منابع مشابه
Tutorial for the WGCNA package for R II. Consensus network analysis of liver expression data, female and male mice 4. Relating consensus modules to external microarray sample information and exporting network analysis results
# Display the current working directory getwd(); # If necessary, change the path below to the directory where the data files are stored. # "." means current directory. On Windows use a forward slash / instead of the usual \. workingDir = "."; setwd(workingDir); # Load the WGCNA package library(WGCNA) # The following setting is important, do not omit. options(stringsAsFactors = FALSE); # Load th...
متن کاملPackage ‘ WGCNA ’ February 15 , 2013
February 15, 2013 Version 1.25-2 Date 2012-12-01 Title Weighted Correlation Network Analysis Author Peter Langfelder and Steve Horvath with contributions by Chaochao Cai,Jun Dong, Jeremy Miller, Lin Song, Andy Yip, and Bin Zhang Maintainer Peter Langfelder Depends R (>= 2.14), stats, impute, grDevices, dynamicT...
متن کاملIdentify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis.
AIM To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis (WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were re...
متن کاملWeighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease.
BACKGROUND The analysis of the potential molecule targets of coronary artery disease (CAD) is critical for understanding the molecular mechanisms of disease. However, studies of global microarray gene co-expression analysis of CAD still remain limited. METHODS Microarray data of CAD (GSE23561) were downloaded from Gene Expression Omnibus, including peripheral blood samples from CAD patients (...
متن کاملTutorials for the WGCNA package for R: WGCNA Background and glossary
WGCNA begins with the understanding that the information captured by microarray experiments is far richer than a list of differentially expressed genes. Rather, microarray data are more completely represented by considering the relationships between measured transcripts, which can be assessed by pair-wise correlations between gene expression profiles. In most microarray data analyses, however, ...
متن کاملTutorial for the WGCNA package for R: I. Network analysis of liver expression data in female mice 3. Relating modules to external information and identifying important genes
3 Relating modules to external clinical traits 2 3.a Quantifying module–trait associations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 3.b Gene relationship to trait and important modules: Gene Significance and Module Membership . . . . 2 3.c Intramodular analysis: identifying genes with high GS and MM . . . . . . . . . . . . . . . . . . . . . . 3 3.d Summary outpu...
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تاریخ انتشار 2011