simulationMCI: Get MCI Scores for randomly selected genes
In BioTIP: BioTIP: An R package for characterization of Biological Tipping-Point

Description Usage Arguments Value Author(s) Examples

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

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

`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.

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

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

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