PCA_tools: Compute a PCA of the different tool used in normalization and...

In jtcasemajor/GENEXPRESSO: Comparison of DEG and coexpression tools

Description

Compute a PCA of the different tool used in normalization and DEG analysis step to discriminate each methods by their found p-values on each genes

Usage

PCA_tools(data.to.comp)

Arguments

data.to.comp

dataframe containing pvalues of genes being differentially expressed, with tools used in row, and genes in columns

Value

Principal component analysis plot with cos2 values for each methods

Examples

# Import the dataset
Data = matrix(runif(5000, 10, 100), ncol=20)
group = paste0(rep(c("control", "case"), each = 10),rep(c(1:10),each = 1))
genes <- paste0(rep(LETTERS[1:25], each=10), rep(c(1:10),each = 1))
colnames(Data) = group
row.names(Data) = genes 

# Compute Pvalues for all the methods 
# res.DEG = tools.DEG.RNAseq.merge(Data)
# Plotting PCA on methods
# PCA_tools(res.DEG)

jtcasemajor/GENEXPRESSO documentation built on Dec. 21, 2021, 4:11 a.m.