ADAPTS (version 1.0.22)

shrinkSigMatrix: Shrink a signature matrix

Description

Use shrinkByKappa and automatic minima detection to reduce a signature matrix. Select the new signature matrix with the minima and the maximum number of genes. There is an inherent difficult in that the condition number will tend to have a second peak at a relatively small number of genes, and then crash so that smallest condition number has more or less one gene.

By default, the algorithm will tend to pick the detected minima with the largest nubmer of genes. aggressiveMin=TRUE will try to find the minimum number of genes that has more genes than the maxima at the smallest number of genes

Usage

shrinkSigMatrix(
  sigMatrix,
  numChunks = 100,
  verbose = FALSE,
  plotIt = FALSE,
  aggressiveMin = TRUE,
  sigGenesList = NULL,
  singleCore = FALSE,
  fastStop = TRUE
)

Value

A list with condition numbers and gene lists

Arguments

sigMatrix

The original signature matrix

numChunks

The number of groups of genes to remove. NULL is all genes (DEFAULT: 100)

verbose

Print out the current chunk as is it's being calculated (DEFAULT: NULL)

plotIt

Set to TRUE to plot (DEFAULT: FALSE)

aggressiveMin

Set to TRUE to aggresively seek the smallest number of genes (DEFAULT: TRUE)

sigGenesList

Set to use precomputed results from shrinkByKappa (DEFAULT: NULL)

singleCore

Set to FALSE to use multiple cores to calculate condition numbers (DEFAULT: FALSE)

fastStop

Halt early when the condition number changes by less than 1 for 3 iterations (DEFAULT: TRUE)

Examples

library(ADAPTS)
LM22 <- ADAPTS::LM22
newSigMat <- shrinkSigMatrix(sigMatrix=LM22[1:100,1:5], numChunks=4, verbose=FALSE, 
plotIt=FALSE, aggressiveMin=TRUE, sigGenesList=NULL, singleCore=TRUE, fastStop=FALSE)