clusterList {TimiRGeN} | R Documentation

## 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))

[Package TimiRGeN version 1.4.0 Index]