DGEAR (version 0.1.4)

DGEAR: 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)

Value

A matrix containing Differentially Expressed Genes(DEGs) detected

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)

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)