simulationMCI: Get MCI Scores for randomly selected genes

simulationMCIR Documentation

Get MCI Scores for randomly selected genes

Description

This function gets the MCI scores for randomly selected features (e.g. transcript ids),

Usage

simulationMCI(
  len,
  samplesL,
  df,
  adjust.size = FALSE,
  B = 1000,
  fun = c("cor", "BioTIP")
)

Arguments

len

An integer that is the length of genes in the CTS (critical transition signal).

samplesL

A list of vectors, whose length is the number of states. Each vector gives the sample names in a state. Note that the vector s (sample names) has to be among the column names of the R object 'df'.

df

A numeric matrix or dataframe of numerics, factor or character. The rows and columns represent unique transcript IDs (geneID) and sample names, respectively

adjust.size

A boolean value indicating if MCI score should be adjust by module size (the number of transcripts in the module) or not. Default FALSE.

B

An integer, setting the permutation with B runs. Default is 1000.

fun

A character chosen between ("cor", "BioTIP"), indicating where an adjusted correlation matrix will be used to calculated the MCI score.

Value

A numeric matrix indicating the MCI scores of permutation. The dimension (row X column) of this matrix is the length of samplesL * B.

Author(s)

Zhezhen Wang zhezhen@uchicago.edu; Xinan H Yang xyang2@uchicago.edu

Examples

counts = matrix(sample(1:100, 18), 3, 9)
colnames(counts) = 1:9
row.names(counts) = c('loci1', 'loci2', 'loci3')
cli = cbind(1:9, rep(c('state1', 'state2', 'state3'), each = 3))
colnames(cli) = c('samples', 'group')
samplesL <- split(cli[, 1], f = cli[, 'group'])
simMCI = simulationMCI(2, samplesL, counts, B=2)
simMCI
#            [,1]      [,2]
#state1  2.924194  2.924194
#state2 20.877138 20.877138
#state3  2.924194  2.924194


xyang2uchicago/NPS documentation built on June 30, 2024, 10:15 p.m.