plotSoftPower: Plot soft power for WGCNA analysis
In RegEnrich: Gene regulator enrichment analysis

Description Usage Arguments Value Examples

Plot soft power and corresponding scale free topology fitting index to find a proper soft power for WGCNA analysis.

plotSoftPower(
  expr,
  rowSample = FALSE,
  weights = NULL,
  powerVector = c(seq(10), seq(12, 20, by = 2)),
  RsquaredCut = 0.85,
  networkType = "unsigned",
  removeFirst = FALSE,
  nBreaks = 10,
  corFnc = WGCNA::cor,
  corOptions = list(use = "p")
)

`expr`	Gene expression data, either a matrix or a data frame. By default, each row represents a gene, each column represents a sample.
`rowSample`	logic. If `TRUE`, each row represents a sample. The default is `FALSE`.
`weights,`	optional observation weights for `expr` to be used in correlation calculation.
`powerVector`	a vector of soft thresholding powers for which the scale free topology fit indices are to be calculated.
`RsquaredCut`	desired minimum scale free topology fitting index R^2. The default is 0.85.
`networkType`	character, network type. Allowed values are (unique abbreviations of) "unsigned" (default), "signed", "signed hybrid". See `adjacency`.
`removeFirst,`	should the first bin be removed from the connectivity histogram? The default is FALSE.
`nBreaks,`	number of bins in connectivity histograms. The default is 10.
`corFnc,`	correlation function to be used in adjacency calculation. The default is the `cor` function in WGCNA.
`corOptions,`	a named list of options to the correlation function specified in corFnc. The default is list(use = "p").

a list of three elements: powerEstimate, fitIndices, and plot. powerEstimate is an estimate of an appropriate soft-thresholding power. fitIndices is a data frame containing the fit indices for scale free topology. The plot is a ggplot object.

data(Lyme_GSE63085)
log2FPKM = log2(Lyme_GSE63085$FPKM + 1)
log2FPKMhi = log2FPKM[rowMeans(log2FPKM) >= 10^-3, , drop = FALSE]
log2FPKMhi = head(log2FPKMhi, 3000) # First 3000 genes for example

softP = plotSoftPower(log2FPKMhi, RsquaredCut = 0.85)
print(softP)