R package WGCNA: Weighted Correlation Network Analysis. Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.
Keywords for this software
References in zbMATH (referenced in 8 articles )
Showing results 1 to 8 of 8.
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- Blum, Yuna; Houée-Bigot, Magalie; Causeur, David: Sparse factor model for co-expression networks with an application using prior biological knowledge (2016)
- Liu, Li; Lei, Jing; Roeder, Kathryn: Network assisted analysis to reveal the genetic basis of autism (2015)
- Qin, Huaizhen; Ouyang, Weiwei: Statistical properties of gene-gene correlations in omics experiments (2015)
- Lu, Xinguo; Deng, Yong; Huang, Lei; Feng, Bingtao; Liao, Bo: A co-expression modules based gene selection for cancer recognition (2014)
- Wang, Y.X.Rachel; Huang, Haiyan: Review on statistical methods for gene network reconstruction using expression data (2014)
- Hardin, Johanna; Garcia, Stephan Ramon; Golan, David: A method for generating realistic correlation matrices (2013)