Get_high_var_genes: Identify highly dispersion differentially expressed genes.

Description Usage Arguments Value Author(s)

View source: R/MASCOT.R

Description

By calculating the difference of dispersion between case and control, MASCOT identifys highly dispersion differentially expressed genes for subsequent analysis.

Usage

1
Get_high_var_genes(expression_profile, sample_info_gene, x.low.cutoff = 0.0125, x.high.cutoff = 5, y.cutoff = 1, do.spike = FALSE, num.bin = 30, plot = FALSE, plot_path = "~/get_high_var_genes.pdf")

Arguments

expression_profile

A dataframe showing the expression profile after all the filterings.

sample_info_gene

A character vector showing the knockout gene of each sample after all the filterings.

x.low.cutoff

Bottom cutoff on x-axis for identifying variable genes

x.high.cutoff

Top cutoff on x-axis for identifying variable genes

y.cutoff

Bottom cutoff on y-axis for identifying variable genes

do.spike

FALSE by default. If TRUE, all genes starting with ^ERCC will be used to normalize the whole data. For most singe cell CRISPR screening data, generally, there are no spike-in genes.

num.bin

Total number of bins to use in the scaled analysis (default is 30)

plot

FALSE by default. If TURE, plot the graphs.

plot_path

The path of graph you plot. It works only when "plot" is TURE.

Value

A dataframe showing the expression profile only for the selected highly dispersion differentially expressed genes.

Author(s)

Bin Duan


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