signedKME: Signed eigengene-based connectivity
In nosarcasm/WGCNA: Weighted Correlation Network Analysis

Description Usage Arguments Details Value Author(s) References

Calculation of (signed) eigengene-based connectivity, also known as module membership.

signedKME(
  datExpr, datME, 
  outputColumnName = "kME", 
  corFnc = "cor", corOptions = "use = 'p'")

`datExpr`	a data frame containing the gene expression data. Rows correspond to samples and columns to genes. Missing values are allowed and will be ignored.
`datME`	a data frame containing module eigengenes. Rows correspond to samples and columns to module eigengenes.
`outputColumnName`	a character string specifying the prefix of column names of the output.
`corFnc`	character string specifying the function to be used to calculate co-expression similarity. Defaults to Pearson correlation. Any function returning values between -1 and 1 can be used.
`corOptions`	character string specifying additional arguments to be passed to the function given by `corFnc`. Use `"use = 'p', method = 'spearman'"` to obtain Spearman correlation.

Signed eigengene-based connectivity of a gene in a module is defined as the correlation of the gene with the corresponding module eigengene. The samples in datExpr and datME must be the same.

A data frame in which rows correspond to input genes and columns to module eigengenes, giving the signed eigengene-based connectivity of each gene with respect to each eigengene.

Steve Horvath

Dong J, Horvath S (2007) Understanding Network Concepts in Modules, BMC Systems Biology 2007, 1:24

Horvath S, Dong J (2008) Geometric Interpretation of Gene Coexpression Network Analysis. PLoS Comput Biol 4(8): e1000117

nosarcasm/WGCNA documentation built on May 28, 2019, 1:01 p.m.