simulationMCI {BioTIP} | R Documentation |
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 |
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