runAcluster: function that run parallel acluster algorithm given a...

In lizhongliu1996/PredictMisc: package that use three methods to predict methylation regions

Description

function that run parallel acluster algorithm given a methylation data frame

Usage

runAcluster(chromeAnnot_df, tBeta_df, minCpGs = 5, ncores = 2)

Arguments

chromeAnnot_df	data frame contains 1 chrome annot information for 450k probes
tBeta_df	a long format BetaValue_df to generate aclusters
minCpGs	minimum number of cpgs within each cluster
ncores	number of cores to do parallel computing

Value

A list of elements containing cg probe names

Examples

## Not run: 
 data(Example_df)
 data(chrome_annot_files)
 BetaTrans_df <- TransposeAssay(
 Example_df[, -1],
 omeNames = "rowNames"
 )
 runAcluster(
    chromeAnnot_df = chrome_annot_files,
    tBeta_df = BetaTrans_df,
    minCpGs = 5,
    ncores = 2
 )

## End(Not run)

lizhongliu1996/PredictMisc documentation built on Aug. 23, 2019, 5:55 a.m.