cnv.data {saasCNV}

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 <[e-mail]>

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.

See Also

vcf2txt

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)