GWASTools (version 1.12.2)

ncdfSetMissingGenotypes: Write a new netCDF or GDS file, setting certain SNPs to missing - deprecated

Description

Deprecated - use setMissingGenotypes

ncdfSetMissingGenotypes copies an existing netCDF genotype file to a new one, setting SNPs in specified regions to missing. gdsSetMissingGenotypes copies an existing GDS genotype file to a new one, setting SNPs in specified regions to missing.

Usage

ncdfSetMissingGenotypes(parent.file, new.file, regions, sample.include=NULL, verbose=TRUE)
gdsSetMissingGenotypes(parent.file, new.file, regions, sample.include=NULL, zipflag="ZIP.max", verbose=TRUE)

Arguments

parent.file

Name of the parent file

new.file

Name of the new file

regions

Data.frame of chromosome regions with columns "scanID", "chromosome", "left.base", "right.base", "whole.chrom".

sample.include

Vector of sampleIDs to include in new.file

zipflag

the compression format for the GDS file, one of "", "ZIP", "ZIP.fast", "ZIP.default", or "ZIP.max"

verbose

Logical value specifying whether to show progress information.

Details

ncdfSetMissingGenotypes and gdsSetMissingGenotypes remove chromosome regions by setting SNPs that fall within the anomaly regions to NA (i.e., the missing value in the netCDF/GDS file). Optionally, entire samples may be excluded from the netCDF/GDS file as well: if the sample.include argument is given, only the scanIDs in this vector will be written to the new file, so the sample dimension will be length(sample.include).

For regions with whole.chrom=TRUE, the entire chromosome will be set to NA for that sample. For other regions, only the region between left.base and right.base will be set to NA.

See Also

ncdfSubset, anomSegStats for chromosome anomaly regions

Examples

## Not run: 
# ncfile <- system.file("extdata", "affy_geno.nc", package="GWASdata")
# nc <- NcdfGenotypeReader(ncfile)
# sample.sel <- getScanID(nc, index=1:10)
# close(nc)
# 
# regions <- data.frame("scanID"=sample.sel[1:3], "chromosome"=c(21,22,23),
#   "left.base"=c(14000000, 30000000, NA), "right.base"=c(28000000, 450000000, NA),
#   whole.chrom=c(FALSE, FALSE, TRUE))
# 
# newnc <- tempfile()
# ncdfSetMissingGenotypes(ncfile, newnc, regions, sample.include=sample.sel)
# file.remove(newnc)
# ## End(Not run)