clusterList {TimiRGeN} | R Documentation |
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.
clusterList(MAE, clusterData, fitCluster, miR_IDs, mRNA_IDs)
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. |
A list containing the genes which fit to each cluster.
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))