qc.DEGs: qc.DEGs function

In wf-frank2019/ne.PCA: The node and edge Prioritization based Community Analysis framework

qc.DEGs function

Description

Data pretreatment and differentially expressed genes identification

Usage

qc.DEGs(expr, group, lowEXP = 1, filter = 0.3, fc = 2, p = 0.05, func = FALSE)

Arguments

expr	data.frame, Expression profile,the row name is the gene name,the column name is the sample name.
group	data.frame, two columns:sample name, sample label,for example:GSM2718949,control.
lowEXP	default 1,Low quality value cutoff,lowEXP must > 0.The expression value less than 'lowEXP' will be seen as missing values.
filter	default 0.3,The proportion of the number of missing values in all samples in one row,the interval is (0,1).A row will be removed if the proportion of missing values in this row is greater than 'filter'.
fc	default 2,Fold Change cutoff,fc must be greater than 1,generally fc is 1.5 or 2 or greater.
p	default 0.05,Adjust p value cutoff,the interval is (0,1),generally p is 0.05 or 0.01 or 0.001.
func	default FALSE,if 'func=TRUE',GO and KEGG pathways Enrichment analysis for DEGs(human genes) will be performed.

Author(s)

Fan Wang

wf-frank2019/ne.PCA documentation built on May 4, 2022, 4:47 p.m.