mutcorcell: mutcorcell

Description Usage Arguments Value Examples

View source: R/mutcorcell.R

Description

Function 'mutcorcell' identifies somatic mutation-driven immune cells by comparing the cell abundance matrix and binary mutations matrix.

Usage

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mutcorcell(
  cellmatrix = cellmatrix,
  mutmatrix = mutmatrix,
  samfdr.cutoff = 0.05,
  nperms = 100,
  fisher.cutoff = 0.05,
  fisher.adjust = FALSE
)

Arguments

cellmatrix

Cell abundance matrix.

mutmatrix

A binary mutations matrix, which can not only come from the maf2matrix function, but also any binary mutations matrix, in which 1 represents any mutation occurs in a particular gene in a particular sample, otherwise the element is 0.

samfdr.cutoff

False Discovery Rate cutoff for output in significant immune cells

nperms

Number of permutations used by SAM to estimate False Discovery Rates

fisher.cutoff

False Discovery Rate(fisher.adjust=TRUE) or P-Value(fisher.adjust=FALSE) cutoff for Fisher's exact test

fisher.adjust

Logical,tell if corrects p-values

Value

A list of four matrices: a binary numerical matrix which shows the immune cells driven by somatic mutant gene; two numerical matrix which show the pvalue and fdr of the immune cells driven by somatic mutant gene; a character matrix which shows the cell responses of the immune cells driven by somatic mutant gene.

Examples

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#get cell abundance matrix which is the result of exp2cell function
cellmatrix<-GetExampleData("cellmatrix")

#get the binary mutations matrix,
mutmatrix<-GetExampleData("mutmatrix")

#perform the function `mutcorcell`.
mutcell<-mutcorcell(cellmatrix = cellmatrix,mutmatrix = mutmatrix)

# The summary for somatic mutations are produced by function `mutcellsummary`.
#summary<-mutcellsummary(mutcell = mutcell,mutmatrix = mutmatrix,cellmatrix=cellmatrix)

# The summary of the immune cells driven by a mutation are produced by function `gene2cellsummary`.
#genecellsummary<-gene2cellsummary(gene="TP53",mutcell=mutcell)

SMDIC documentation built on Nov. 13, 2020, 5:06 p.m.