View source: R/MakeSigMatrix.R
rankByT | R Documentation |
Use a t-test to rank to features for each cell type
gList <- rankByT(geneExpr, qCut=0.3)
rankByT( geneExpr, qCut = 0.3, oneCore = FALSE, secondPval = TRUE, remZinf = FALSE, reqRatGT1 = FALSE )
geneExpr |
The gene expression data |
qCut |
(DEFAULT: 0.3) |
oneCore |
Set to TRUE to disable paralellization (DEFAULT: FALSE) |
secondPval |
Set to TRUE to use p-Values as a second sort criteria (DEFAULT: TRUE) |
remZinf |
Set to TRUE to remove any ratio with zero or infinity. Good for scRNAseq. (DEFAULT: FALSE) |
reqRatGT1 |
Set to TRUE to remove any gene with a ratio with less than 1. Good for scRNAseq. (DEFAULT: FALSE) |
a list of cell types with data frames ranking genes
#This toy example treats the LM22 deconvolution matrix as if it were all of the data # For a real example, look at the vignette or comments in exprData, fullLM22, small LM22 library(ADAPTS) fullLM22 <- ADAPTS::LM22[1:200, 1:8] #Make a fake signature matrix out of 100 genes and the first 8 cell types smallLM22 <- fullLM22[1:100, 1:8] #Make fake data representing two replicates of purified Mast.cells exprData <- ADAPTS::LM22[1:200, c("Mast.cells.resting","Mast.cells.activated")] colnames(exprData) <- c("Mast.cells", "Mast.cells") #Fake source data with replicates for all purified cell types. # Note in this fake data set, many cell types have exactly one replicate fakeAllData <- cbind(fullLM22, as.data.frame(exprData)) gList <- rankByT(geneExpr = fakeAllData, qCut=0.3, oneCore=TRUE, reqRatGT1=FALSE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.