snp.cnv.data {saasCNV} | R Documentation |
Construct Data Frame for CNV Inference with SNP Array Data
Description
Transform LRR and BAF information into log2ratio and log2mBAF that we use for joint segmentation and CNV calling.
Usage
snp.cnv.data(snp, min.chr.probe = 100, verbose = FALSE)
Arguments
snp |
a data frame with LRR and BAF information from SNP array. See the example below for details. |
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 |
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.
See Also
Examples
## Not run:
## an example data with LRR and BAF information
url <- "https://zhangz05.u.hpc.mssm.edu/saasCNV/data/snp_table.txt.gz"
tryCatch({download.file(url=url, destfile="snp_table.txt.gz")
}, error = function(e) {
download.file(url=url, destfile="snp_table.txt.gz", method="curl")
})
## If download.file fails to download the data, please manually download it from the url.
snp_table <- read.delim(file="snp_table.txt.gz", as.is=TRUE)
snp.data <- snp.cnv.data(snp=snp_table, min.chr.probe=100, verbose=TRUE)
## see how seq.data looks like
url <- "https://zhangz05.u.hpc.mssm.edu/saasCNV/data/snp.data.RData"
tryCatch({download.file(url=url, destfile="snp.data.RData")
}, error = function(e) {
download.file(url=url, destfile="snp.data.RData", method="curl")
})
## If download.file fails to download the data, please manually download it from the url.
load("snp.data.RData")
head(snp.data)
## End(Not run)