createClusters2: createClusters2

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

Description

Creates clusters from a dataframe of mRNAs and miRs. This function should primarily be used when analysing data that has not gone through pair-wise DE. This function will create clusters from longitudinal temporal patterns. createClusters2 will create 3 data files. 1) Clusters will contain cluster logistics information and will be stored as metadata, 2) MfuzzData will contain fuzzy clustering information and will be stored as an experiment, 3) ClusterData will contain cluster-pathway fit information and will be stored as an assay.

Usage

createClusters2(MAE, genetic_data, noClusters)

Arguments

MAE	MultiAssayExperiment which will store the results from createClusters2.
genetic_data	A dataframe with miR and mRNA information together. This is the output from the combineGenes function and will be stored as an assay within the MAE used in the combineGenes function.
noClusters	How many clusters should be generated? Default is 5.

Value

3 new objects in the input MAE. Clusters(metadata): A list to be used as the input in checkClusters and quickFuzz. MfuzzData(ExperimentList): An ExpressionSet object to be used as input for quickFuzz. ClusterData(assay): An assay to be used as input for returnCluster.

Examples

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

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

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

MAE <- createClusters2(MAE = MAE, genetic_data = assay(MAE, 3))

TimiRGeN documentation built on April 17, 2021, 6:03 p.m.