methstats {methylPipe} | R Documentation

## Exploratory statistics of samples in BSdataSet object

### Description

Exploratory methylation statistics of samples in BSdataSet object.

### Usage

    ## S4 method for signature 'methylPipe,BSdataSet'
    methstats(object, chrom, mcClass='mCG', minC=1, coverage=1, pval=1, Nproc=1)

### Arguments

`object` | An object of class BSdataSet
`chrom` | character; either NULL or an object of class character
`mcClass` | character; the mC sequence context to be considered, one of all, mCG, mCHG or mCHH
`minC` | numeric; the minumum number of reads with C (DNA-methylation events) at a given cytosine genomic position
`coverage` | numeric; the minimum number of total reads at a given cytosine genomic position
`pval` | numeric; the minimum binomial pValue for an mC call at a given cytosine genomic position
`Nproc` | numeric; the number of processors to use, one chromosome is ran for each processor

### Details

The function provides basic statistical methods which computes descriptive statistics, correlation matrix and clustering of samples within the BSdataSet.

### Value

A list with slots named descriptive_stats and correlation_mat.

### Author(s)

Kamal Kishore

### Examples

    require(BSgenome.Hsapiens.UCSC.hg18)
    uncov_GR <- GRanges('chr20', IRanges(14350, 18349))
    H1data <- system.file('extdata', 'H1_chr20_CG_10k_tabix_out.txt.gz', package='methylPipe')
    H1.db <- BSdata(file=H1data, uncov=uncov_GR, org=Hsapiens)
    IMR90data <- system.file('extdata', 'IMR90_chr20_CG_10k_tabix_out.txt.gz', package='methylPipe')
    IMR90.db <- BSdata(file=IMR90data, uncov=uncov_GR, org=Hsapiens)
    H1.IMR90.set <- BSdataSet(org=Hsapiens, group=c("C","C","E","E"), IMR_1=IMR90.db,
    IMR_2=IMR90.db, H1_1=H1.db,H1_2=H1.db)
    stats_res <- methstats(H1.IMR90.set,chrom="chr20",mcClass='mCG', Nproc=1)
    stats_res

[Package methylPipe version 1.16.0 Index]