ClustAndGO: ClustAndGO

In askomics/askoR: Differential Expression Analysis using 'edgeR'

ClustAndGO

Description

Clusterize genes with same profile, proceed to GO-enrichment on clusters, search for contrasts enriched with genes of specific clusters, and identify intersections of DE list genes

• Graphs of clusters (heatmap and boxplot)

• Expression profiles in each cluster

• GO enrichments in each cluster

• Files with gene description of each significant enriched GO

• Over-representation of genes of each cluster in each contrast

• Intersections of DE list genes in each cluster

Usage

ClustAndGO(asko_norm, resDEG, parameters, data, list = NULL, title = NULL)

Arguments

asko_norm	large DGEList with normalized counts by GEnorm function.
resDEG	data frame contains for each contrast the significance expression (1/0/-1) for all genes coming from DEanalysis function.
parameters	list that contains all arguments charged in Asko_start.
data	list contain all data and metadata (DGEList, samples descritions, contrast, design and annotations)
list	gene list of interest if you want to apply ClustAndGO function on a specific gene list
title	name of the gene list if you want to apply ClustAndGO function on a specific gene list

Value

data frame with clusters of each gene

Note

Remember to read the Wiki section in https://github.com/askomics/askoR/wiki

Examples

## Not run: 
   clust<-ClustAndGO(asko_norm, resDEG, parameters, data)
   # OR
   clust<-ClustAndGO(asko_norm, resDEG, parameters, data, list, title)

## End(Not run)

askomics/askoR documentation built on Jan. 17, 2025, 6:23 p.m.