Calculation of (signed) eigengene-based connectivity, also known as module membership.
signedKME(
datExpr, datME,
outputColumnName = "kME",
corFnc = "cor", corOptions = "use = 'p'")a data frame containing the gene expression data. Rows correspond to samples and columns to genes. Missing values are allowed and will be ignored.
a data frame containing module eigengenes. Rows correspond to samples and columns to module eigengenes.
a character string specifying the prefix of column names of the output.
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.
character string specifying additional arguments to be passed to the function given
by corFnc. Use "use = 'p', method = 'spearman'" to obtain Spearman correlation.
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.
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.
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