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FastCAR
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Added recommended empty cutoff function

This commit is contained in:
Marijn 2020-04-27 13:40:04 +02:00
parent 48dc9d81e6
commit c457e087be
1 changed files with 33 additions and 15 deletions
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48
R/FastCAR_Base.R
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@ -7,7 +7,8 @@
# empty droplets and removing per gene the highest value found in the ambient
# RNA if it's found to contaminate more than a certain threshold of droplets
###############################################################################
# This file contains base functions
# TODO
#
###############################################################################
library(Matrix)
library(Seurat)
@ -22,6 +23,14 @@ library(qlcMatrix)
# p: the where in 'i' and 'x' a new column starts
# Dimnames: The names of the rows and columns
remove.background = function(geneCellMatrix, ambientRNAprofile){
# do some input checks first
if(!("dgCMatrix" %in% class(geneCellMatrix))){
cat("geneCellMatrix should be a sparse matrix of the \"dgCMatrix\" class")
stop()
}
# Here is the actual functionality
for(gene in names(ambientProfile[ambientProfile > 0])){
# Determine the locations where the gene is not zero, therefore referenced in i
iLocs = which(geneCellMatrix@Dimnames[[1]] == gene)
@ -72,20 +81,23 @@ read.full.matrix = function(fullFolderLocation){
}
##############
# Turns out that cellranger output looks different from WriteMM output and Read10X can't read the latter
# TODO
# Commented out until I find a fix
write.corrected.matrix = function(correctedMatrix, folderLocation, correctedSignal){
dir.create(folderLocation)
writeMM(obj = correctedMatrix, file=paste(folderLocation, "/matrix.mtx", sep = ""))
# save genes and cells names
write(x = rownames(correctedMatrix), file = paste(folderLocation, "/genes.tsv", sep = ""))
write(x = colnames(correctedMatrix), file = paste(folderLocation, "/barcodes.tsv", sep = ""))
correctedSignal = correctedSignal[correctedSignal > 0]
write.table(list(correctedSignal), file = paste(folderLocation, "/genesCorrectedFor.csv", sep = ""), row.names = TRUE, col.names = FALSE)
}
# write.corrected.matrix = function(correctedMatrix, folderLocation, correctedSignal){
# dir.create(folderLocation)
#
# writeMM(obj = correctedMatrix, file=paste(folderLocation, "/matrix.mtx", sep = ""))
#
# # save genes and cells names
# write(x = rownames(correctedMatrix), file = paste(folderLocation, "/genes.tsv", sep = ""))
# write(x = colnames(correctedMatrix), file = paste(folderLocation, "/barcodes.tsv", sep = ""))
#
# correctedSignal = correctedSignal[correctedSignal > 0]
# write.table(list(correctedSignal), file = paste(folderLocation, "/genesCorrectedFor.csv", sep = ""), row.names = TRUE, col.names = FALSE)
#
# }
# describe the number of genes identified in the background
# and the number of genes failing the contaminiation chance threshold
@ -132,7 +144,13 @@ plot.ambient.profile = function(ambientProfile){
ylab = "Genes identified as contamination")
}
# I noticed that the number of genes removed tends to even out over time
# Test whether the point where this first happens is a good empty cutoff point
recommendedRemoval = function(ambientProfile){
highestNumberOfGenes = max(ambientProfile[,3])
firstOccurence = match(highestNumberOfGenes, ambientProfile[,3])
return(as.numeric(rownames(ambientProfile[firstOccurence,])))
}