learnPatterns: Learn average and variability patterns

In hshdndx/new-to-CNV: patternCNV: a versatile tool for detecting copy number changes from exome-seq data

Description

This function is used to learn patterns from normal/reference samples

Usage

learnPatterns(session.name, refdata.name, sample.type = NULL, 
                     episl = 1, bin.size = 10, excluded.sample.name = NULL)

Arguments

session.name	an object of PatCNVSession-class
refdata.name	an object of PatCNVData-class of reference samples, which should typically be normal or Germline samples
sample.type	a character vector of sample type defined in sample information file: e.g. "Germline". A value of NULL instructs the function to select all the samples regardless sample types
episl	a small value adding to coverage to avoid doing log-transform on zero
bin.size	numeric value of exon-level bin-size
excluded.sample.name	a character vector containing sample names that are excluded for pattern training

Details

Average- and variability- pattern WIG files are expected to be generated under txt_output_DIF defined in configuration file, along with two other baseline coverage files.

Author(s)

Chen Wang

See Also

scanMultiCovg; computeMultiCNV

Examples

 
#=== load a simulation example
config.filename <- "sim1.ini"
makeSimulation(config.filename)
sim.session <- createSession(config.filename)

#=== print session information
summary(sim.session)

#=== scan coverages of multiple samples
germline.data <- scanMultiCovg(session.name=sim.session)

#=== learn average- and variability-patterns
learnPatterns(session.name=sim.session,refdata.name=germline.data)

#=== print session information; notice that pattern files have been generated
summary(sim.session)

hshdndx/new-to-CNV documentation built on May 17, 2019, 5:55 p.m.