generateGDS: Produce CNV-GDS for the phenotyped samples

In CNVRanger: Summarization and expression/phenotype association of CNV ranges

Description

Function to produce the GDS file in a probe-wise fashion for CNV genotypes. The GDS file which is produced also incorporates one phenotype to be analyzed. If several phenotypes are enclosed in the ‘phen.info’ object, the user may specify the phenotype to be analyzed with the ‘lo.phe’ parameter. Only diploid chromosomes should be included.

Usage

generateGDS(
  phen.info,
  freq.cn = 0.01,
  snp.matrix = FALSE,
  lo.phe = 1,
  chr.code.name = NULL,
  genotype.nodes = c("CNVGenotype", "CNVgenotypeSNPlike"),
  coding.translate = NULL,
  n.cor = 1
)

Arguments

phen.info	Returned by setupCnvGWAS
freq.cn	Minimum frequency. Default is 0.01 (i.e. 1%)
snp.matrix	Only FALSE implemented. If TRUE, B allele frequencies (BAF) and SNP genotypes would be used to reconstruct CNV-SNP genotypes - under development
lo.phe	The phenotype to be analyzed in the PhenInfo$phenotypesSam dataframe
chr.code.name	A data-frame with the integer name in the first column and the original name in the second for each chromosome previously converted to numeric
genotype.nodes	Nodes with CNV genotypes to be produced in the gds file. Use 'CNVGenotype' for dosage-like genotypes (i.e. from 0 to Inf). Use 'CNVgenotypeSNPlike' alongside for SNP-like CNV genotype in a separated node (i.e. '0, 1, 2, 3, 4' as '0/0, 0/1, 1/1, 1/2, 2/2').
coding.translate	For 'CNVgenotypeSNPlike'. If NULL or unrecognized string use only biallelic CNVs. If 'all' code multiallelic CNVs as 0 for loss; 1 for 2n and 2 for gain.
n.cor	Number of cores

Value

probes.cnv.gr Object with information about all probes to be used in the downstream CNV-GWAS. Only numeric chromosomes

Author(s)

Vinicius Henrique da Silva <[e-mail]>

Examples

# Load phenotype-CNV information
data.dir <- system.file("extdata", package="CNVRanger")

phen.loc <- file.path(data.dir, "Pheno.txt")
cnv.out.loc <- file.path(data.dir, "CNVOut.txt")
map.loc <- file.path(data.dir, "MapPenn.txt")

phen.info <- setupCnvGWAS('Example', phen.loc, cnv.out.loc, map.loc)

# Construct the data-frame with integer and original chromosome names 
 
# Define chr correspondence to numeric, if necessary
df <- '16 1A
25 4A
29 25LG1
30 25LG2
31 LGE22'

chr.code.name <- read.table(text=df, header=FALSE)
probes.cnv.gr <- generateGDS(phen.info, chr.code.name=chr.code.name)

CNVRanger documentation built on Dec. 12, 2020, 2 a.m.