Get_high_varGenes: Identify highly dispersion differentially expressed genes.

In bm2-lab/MASCOT: Model-based Understanding of SIngle-cell CRISPR screening

Identify highly dispersion differentially expressed genes.

Description

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

Usage

Get_high_varGenes(expression_profile, perturb_information, x.low.cutoff = 0.01, y.cutoff = 0, 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.
perturb_information	A character vector showing the perturbation of each sample after all the filterings.
x.low.cutoff	Bottom cutoff on x-axis for identifying variable genes
y.cutoff	Bottom cutoff on y-axis for identifying variable genes
num.bin	Number of bins to use in the scaled analysis (default is 30)
plot	FALSE by default. If TRUE, plot the graphs.
plot_path	The save path of the graph you plot. It works only when the parameter "plot" is TRUE.

Value

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

Author(s)

Bin Duan

bm2-lab/MASCOT documentation built on April 19, 2024, 4:35 p.m.