cpg.qc {CpGassoc}

Performs quality control on Illumina data.

Description

cpg.qc is designed to perform quality control on Illumina data prior to analysis. In addition to the matrix of beta values, this function requires as input matrices of Signal A, Signal B, and detection p-values. It can also set to NA datapoints with detection p-values exceeding a user-specified cutoff, and can remove samples or sites that have a missing rate above a user-specified value. Finally, users can opt to compute beta values as M/(U+M) or M/(U+M+100). Illumina suggested previous array versions use a 2000 signal value as a possible cutoff, but this is not appropriate for EPICv2 and beyond. Older versions of CpGassoc use the 2000 signal value cutoff. Default is now set to 0.

Usage

cpg.qc(beta.orig,siga,sigb,pval,p.cutoff=.001,cpg.miss=NULL,sample.miss=NULL,
constant100=FALSE,sig.return=FALSE,low.sig.remove=FALSE,low.sig.cutoff=0)

Arguments

beta.orig

The original beta values matrix.

siga

The unmethylated signals matrix.

sigb

The methylated signals matrix.

pval

A matrix of detection p-values. pval should have the same dimension as the beta values and signals: one row for each site and one column for each individual.

p.cutoff

The user-specified cutoff for detection p-values (default=.001).

cpg.miss

Optional cutoff value. If specified, cpg.qc will remove cpg sites where the proportion of missing values exceeds this cutoff.

sample.miss

Optional cutoff value. If specified, cpg.qc will remove samples where the proportion of missing values exceeds this cutoff.

constant100

Logical. If true, the new beta values will be calculated as M/(U+M+100); if false (default) they will be calculated as M/(U+M).

sig.return

Logical. If true, cpg.qc returns a list with the betas and the qced signal data as well.

low.sig.remove

Logical. If true, cpg.qc will remove samples that have low intensity (mean signal intensity less than half of the overall median or low.sig.cutoff).

low.sig.cutoff

Numeric. Value to be used. by low.sig.cutoff

Details

It is important that all the matrices listed above (pval, siga, sigb, beta.orig) are ordered similarly with respect to samples and CpG sites.

Value

cpg.qc returns a new matrix of beta values that has been subjected to the specified quality control filters. This matrix can be input directly into cpg.assoc.

Author(s)

Barfield, R.; Conneely, K.; Kilaru,V.
Maintainer: R. Barfield: <[e-mail]>

See Also

cpg.work cpg.perm plot.cpg scatterplot cpg.combine cpg.assoc