SnpArrayExperiment-class: A RangedSummarizedExperiment-derived class of marker-level...

In rscharpf/VanillaICE: A Hidden Markov Model for high throughput genotyping arrays

Description

Constructor for SnpArrayExperiment

Usage

SnpArrayExperiment(cn, baf, rowRanges = GRanges(),
  colData = DataFrame(), isSnp = logical(), ...)

## S4 method for signature 'missing'
SnpArrayExperiment(cn, baf, rowRanges = GRanges(),
  colData = DataFrame(), isSnp = logical(), ...)

## S4 method for signature 'matrix'
SnpArrayExperiment(cn, baf, rowRanges = GRanges(),
  colData = DataFrame(row.names = colnames(cn)), isSnp = logical(),
  ...)

Arguments

cn	matrix of copy number estimates (e.g., log R ratios)
baf	matrix of B allele frequencies
rowRanges	GRanges object for SNPs/nonpolymorphic markers
colData	DataFrame containing sample-level covariates
isSnp	logical vector indicating whether marker is a SNP
...	additional arguments passed to SummarizedExperiment() constructor function

Examples

## empty container

data(snp_exp) # example

SnpArrayExperiment(cn=lrr(snp_exp), baf=baf(snp_exp),
                   rowRanges=rowRanges(snp_exp))

rscharpf/VanillaICE documentation built on May 15, 2019, 5:51 p.m.