FilterCellMutation: Filter out low expressed gene and high dropout cells based on...

In zhouzilu/DENDRO: Dna based EvolutioNary tree preDiction by scRna-seq technOlogy

Description

This function filter out low expressed gene (cut.off.VAF) and high dropout cells (cut.off.sd) based on read counts and plot out the summary distributions.

Usage

FilterCellMutation(X, N, Z, Info = NULL, label = NULL, cut.off.VAF = 0.05, cut.off.sd = 5, plot = TRUE)

Arguments

X	An matrix contains variants allele read counts across cell (column) and loci (row).
N	An matrix contains total allele read counts across cell (column) and loci (row).
Z	An mutation indicator matrix (1 for mutation, 0 for normal) across cell (column) and loci (row).
Info	Mutation loci information. Matrix with row number same to number of loci and column number > 1. This is optional. Default NULL
label	An integer 1D vector that decide the label color by type. The label can be assigned due to piror information such as individuals or site. Default NULL, where no color label.
cut.off.VAF	Variant allele frequency (VAF, sum(Z)/length(Z) ) filter threshold. Variants with variants allele frequency less than cut.off.VAF (too rare) or greater than 1-cut.off.VAF (too common) are filtered out. Default 0.05
cut.off.sd	Cell total expression (sum(N)) filter threshold. Cells with total expression less than mean(N)-cut.off.sd*sd(N) (too small) or greater than mean(N)+cut.off.sd*sd(N) (double or triplet) are filtered out. Default 5
plot	TRUE or FALSE, decide whether to plot the distribution and cut off (red line). Default value is TRUE.

Value

List of filtered matrix

X	Input X after filtering
N	Input N after filtering
Z	Input Z after filtering
Info	Input Info after filtering
label	Input label after filtering

Author(s)

Zilu Zhou

Examples

data("DENDRO_demo")
demo_qc = FilterCellMutation(demo$X,demo$N,demo$Z,demo$Info,demo$label)

zhouzilu/DENDRO documentation built on May 21, 2020, 8 p.m.