cpgDiscretization: Discretize the CpG methylation values to align with single...

In scmeth: Functions to conduct quality control analysis in methylation data

Description

In single cell analysis overwhelmingly large number of CpGs have binary methylation Due to errors in sequencing and amplification many CpGs tend to have non-binary methylation. Hence this function catergorizes the non-binary CpGs as methylated if the methyation is above 0.8 and unmethylated if the methylation is below 0.2

Usage

cpgDiscretization(bs, subSample = 1e+06, offset = 50000,
  coverageVec = NULL)

Arguments

bs	bsseq object
subSample	number of CpGs to subsample. Default value is 1000000.
offset	how many CpGs to offset when subsampling Default value is set to be 50000, i.e. first 50000 CpGs will be ignored in subsampling.
coverageVec	If coverage vector is already calculated provide it to speed up the process

Value

meth discretized methylation matrix

discard total number of removed CpGs from each sample

Percentage of CpGs discarded compared to the total number of CpGs

Examples

directory <- system.file("extdata/bismark_data", package='scmeth')
bs <- HDF5Array::loadHDF5SummarizedExperiment(directory)
cpgDiscretization(bs)

scmeth documentation built on Nov. 8, 2020, 6:21 p.m.