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Last data update: 2014.03.03

R: Construct Data Frame for CNV Inference with NGS Data

cnv.data

R Documentation

Construct Data Frame for CNV Inference with NGS Data

Description

Transform read depth information into log2ratio and log2mBAF that we use for joint segmentation and CNV calling.

Usage

cnv.data(vcf, min.chr.probe = 100, verbose = FALSE)

Arguments

`vcf`	a data frame constructed from a vcf file. See `vcf2txt`.
`min.chr.probe`	the minimum number of probes tagging a chromosome for it to be passed to the subsequent analysis.
`verbose`	logical. If more details to be output. Default is `FALSE`.

Value

A data frame containing the log2raio and log2mBAF values for each probe site.

Author(s)

Zhongyang Zhang <zhongyang.zhang@mssm.edu>

References

Staaf, J., Vallon-Christersson, J., Lindgren, D., Juliusson, G., Rosenquist, R., Hoglund, M., Borg, A., Ringner, M. (2008) Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios. BMC bioinformatics, 9:409.

Examples

## load a data frame constructed from a vcf file with vcf2txt

## Not run: 
## download vcf_table.txt.gz
url <- "https://zhangz05.u.hpc.mssm.edu/saasCNV/data/vcf_table.txt.gz"
tryCatch({download.file(url=url, destfile="vcf_table.txt.gz")
         }, error = function(e) {
          download.file(url=url, destfile="vcf_table.txt.gz", method="curl")
         })
## If download.file fails to download the data, please manually download it from the url.

vcf_table <- read.delim(file="vcf_table.txt.gz", as.is=TRUE)
seq.data <- cnv.data(vcf=vcf_table, min.chr.probe=100, verbose=TRUE)

## End(Not run)

## see how seq.data looks like
data(seq.data)
head(seq.data)