clusterList: clusterList

In Krutik6/TimiRGeN: Time sensitive microRNA-mRNA integration, analysis and network generation tool

clusterList

Description

clusterList will transform clusters created by createClusters2 into lists based on which genes associate most to each cluster. Genes which associate with a cluster are determined by the fitCluster parameter in the function.

Usage

clusterList(MAE, clusterData, fitCluster, miR_IDs, mRNA_IDs)

Arguments

MAE	MultiAssayExperiment which will store the results from createClusters.
clusterData	A dataframe which contains cluster-pathway fit scores and is stored as an assay within the MAE used in the createClusters2 function.
fitCluster	Integer from 0-1. How well should genes fit into a cluster? Default is 0.5.
miR_IDs	miR_ensembl or miR_entrez. Use a getIDsMir function to acquire this. This will be stored as an assay in the MAE used in a getIdsMir function.
mRNA_IDs	mRNA_ensembl or mRNA_entrez. Use a getIDsMrna function to acquire this. This will be stored as an assay in the MAE used in a getIdsMrna function.

Value

A list containing the genes which fit to each cluster.

Examples

library(org.Hs.eg.db)

data(long_data)

miRNA <- long_data[c(1:105),]

mRNA <- long_data[-c(1:105),]

MAE <- startObject(miR = miRNA, mRNA = mRNA)

MAE <- getIdsMir(MAE, assay(MAE, 1), orgDB = org.Hs.eg.db, 'hsa')

MAE <- getIdsMrna(MAE, assay(MAE, 2), mirror = 'useast', 'hsapiens',
                  orgDB = org.Hs.eg.db)

MAE <- combineGenes(MAE, miR_data = assay(MAE, 1),
                    mRNA_data = assay(MAE, 2))

MAE <- createClusters2(MAE = MAE, genetic_data = assay(MAE, 9),
                       noClusters =2)

MAE <- clusterList(MAE = MAE, clusterData = assay(MAE, 11), fitCluster = 0.5,
                   miR_IDs = assay(MAE, 3),
                   mRNA_IDs = assay(MAE, 7))

Krutik6/TimiRGeN documentation built on Jan. 27, 2024, 7:46 p.m.