generateGDS {CNVRanger} | R Documentation

## Produce CNV-GDS for the phenotyped samples

### 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 <vinicius.dasilva@wur.nl>

### 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)

[Package CNVRanger version 1.3.6 Index]