DGEAR: Differential Gene Expression Analysis with R

In DGEAR: Differential Gene Expression Analysis with R

Differential Gene Expression Analysis with R

Description

Main function which incorporates results from five statistical models and detects DEGs through majority voting.

Usage

DGEAR(dataframe, con1, con2, exp1, exp2, alpha, votting_cutoff)

Arguments

dataframe	A matrix containing the gene expression data
con1	Starting column of the control of the expression data
con2	Ending column of the control of the expression data
exp1	Starting column of the experiment of the expression data
exp2	Ending column of the experiment of the expression data
alpha	Value of significance level ranging from 0 to 1 (0.05 states 5 % significance)(Default = 0.05).
votting_cutoff	A numeric value serves as Majority voting (Default = 2)

Details

To use this tool the necessary parameters are con1 = Control start column, con2 = Control end column, exp1 = Experiment start column, exp2 = Experiment end column, alpha = Value of significance level, voting_cutoff = Majority voting value (not more than 5, since there are 5 statistical methods which take part in the majority voting)

Value

A matrix containing Differentially Expressed Genes(DEGs) detected

Examples

library(DGEAR)
data("gene_exp_data")
DGEAR(dataframe = gene_exp_data, con1 = 1, con2 = 10,
  exp1 = 11, exp2 = 20, alpha = 0.05, votting_cutoff = 2)

DGEAR documentation built on June 27, 2024, 1:07 a.m.