Cell_qc: Quality control for single-cell CRISPR screening data.

In BinDuan/MASCOT: Model-based Analysis of Single cell CRISPR knockOuT screening

Description

MASCOT evaluates the cell quality by three factors, i.e. the number of genes detected (default 500), the number of unique molecular identifier induced (default 1500), and the percentage of mitochondrial genes detected (default 10% among all the detected genes). Only cells with the first two factors above the thresholds and the third factor below the threshold are retained.

Usage

Cell_qc(expression_profile, sample_info_gene, species = "Hs", gene_low = 500, gene_high = 10000, mito_high = 0.1, umi_low = 1500, umi_high = Inf, plot = FALSE, plot_path = "~/quality_control.pdf")

Arguments

expression_profile	A dataframe showing the expression profile.
sample_info_gene	A character vector showing the knockout gene of each sample. The vector's column name is the sample name.
species	The species the cells belong to. Currently species="Hs" for homo sapiens or species="Mm" for mus musculus are available.
gene_low	The minimun gene number for cells. Cells with genes below this threshold are filtered(default 500).
gene_high	The maximum gene number for cells. cells with genes above this threshold are filtered(default 10000).
mito_high	The maximum percentage of mitochondrial genes detected(default 10% among all the detected genes).
umi_low	The minimum number of unique molecular identifier induced (default 1500).
umi_high	The maximun number of unique molecular identifier induced (default Inf)
plot	FALSE by default. If TURE, plot the graph.
plot_path	The path of the graph you plot. It works only when the parameter "plot" is TRUE.

Value

expression_profile_qc	A dataframe showing expression profile after quality control.
sample_info_gene_qc	A character vector showing the knockout gene of each sample after quality control.

Author(s)

Bin Duan

References

http://satijalab.org/seurat/

BinDuan/MASCOT documentation built on May 23, 2019, 2:42 p.m.