buildSeed: Build a deconvolution seed matrix

In yxinyi2/ADAPTS1.0.3: Automated Deconvolution Augmentation of Profiles for Tissue Specific Cells

Description

Use ranger to select features and build a genesInSeed gene matrix

Usage

buildSeed(
  trainSet,
  genesInSeed = 200,
  groupSize = 30,
  randomize = TRUE,
  num.trees = 1000,
  plotIt = FALSE,
  trainSet.3sam = NULL,
  trainSet.30sam = NULL
)

Arguments

trainSet	Each row is a gene, and each column is an example of a particular cell type, ie from single cell data
genesInSeed	The maximum number of genes in the returned seed matrix (DEFAULT: 200)
groupSize	The number of groups to break the trainSet into by ADAPTS::scSample (DEFAULT: 30)
randomize	Set to TRUE randomize the sets selected by ADAPTS::scSample (DEFAULT: TRUE)
num.trees	The number of trees to be used by ranger (DEFAULT: 1000)
plotIt	Set to TRUE to plot (DEFAULT: FALSE)
trainSet.3sam	Optional pre-calculated ADAPTS::scSample(trainSet, groupSize = 3) (DEFAULT: NULL)
trainSet.30sam	Optional pre-calculated ADAPTS::scSample(trainSet, groupSize=groupSize, randomize=randomize) (DEFAULT: NULL)

Value

A list with condition numbers and gene lists

Examples

library(ADAPTS)
ct1 <- runif(1000, 0, 100)
ct2 <- runif(1000, 0, 100)
dataMat <- cbind(ct1, ct1, ct1, ct1, ct1, ct1, ct2, ct2, ct2, ct2)
rownames(dataMat) <- make.names(rep('gene', nrow(dataMat)), unique=TRUE)
noise <- matrix(runif(nrow(dataMat)*ncol(dataMat), -2, 2), nrow = nrow(dataMat), byrow = TRUE)
dataMat <- dataMat + noise
newSigMat <- buildSeed(trainSet=dataMat)

yxinyi2/ADAPTS1.0.3 documentation built on Aug. 5, 2020, 12:09 a.m.