plotScoringModel: plotVariantsForCNV

In jpuntomarcos/CNVfilteR: Identifies false positives of CNV calling tools by using SNV calls

plotVariantsForCNV

Description

Plots scoring model used for CNV duplications

Usage

plotScoringModel(
  expected.ht.mean,
  expected.dup.ht.mean1,
  expected.dup.ht.mean2,
  sigmoid.c1,
  sigmoid.c2.vector
)

Arguments

expected.ht.mean	Expected heterozygous SNV/indel allele frequency
expected.dup.ht.mean1	Expected heterozygous SNV/indel allele frequency when the variant IS NOT in the same allele than the CNV duplication call
expected.dup.ht.mean2	Expected heterozygous SNV/indel allele frequency when the variant IS in the same allele than the CNV duplication call
sigmoid.c1	Sigmoid c1 parameter
sigmoid.c2.vector	Vector containing sigmoid c2 parameters for the six sigmoids functions

Value

nothing

Examples

# Load CNVs data
cnvs.file <- system.file("extdata", "DECoN.CNVcalls.csv", package = "CNVfilteR", mustWork = TRUE)
cnvs.gr <- loadCNVcalls(cnvs.file = cnvs.file, chr.column = "Chromosome", start.column = "Start", end.column = "End", cnv.column = "CNV.type", sample.column = "Sample")

# Load VCFs data
vcf.files <- c(system.file("extdata", "variants.sample1.vcf.gz", package = "CNVfilteR", mustWork = TRUE),
               system.file("extdata", "variants.sample2.vcf.gz", package = "CNVfilteR", mustWork = TRUE))
vcfs <- loadVCFs(vcf.files, cnvs.gr = cnvs.gr)

# Filter CNVs
results <- filterCNVs(cnvs.gr, vcfs)

# Plot scoring model for duplication CNVs
p <- results$filterParameters
plotScoringModel(expected.ht.mean = p$expected.ht.mean, expected.dup.ht.mean1 = p$expected.dup.ht.mean1,
                  expected.dup.ht.mean2 = p$expected.dup.ht.mean2, sigmoid.c1 = p$sigmoid.c1, sigmoid.c2.vector = p$sigmoid.c2.vector)

jpuntomarcos/CNVfilteR documentation built on Oct. 6, 2023, 12:37 a.m.