seqOptimize: Optimize the Storage of Data Array
In SeqArray: Data management of large-scale whole-genome sequence variant calls

Description Usage Arguments Details Value Author(s) See Also Examples

Transpose data array or matrix for possibly higher-speed access.

1 2	seqOptimize(gdsfn, target=c("chromosome", "by.sample"), format.var=TRUE, cleanup=TRUE, verbose=TRUE)

`gdsfn`	the file name of GDS
`target`	"chromosome", "by.sample"; see details
`format.var`	a character vector for selected variable names, or `TRUE` for all variables, according to "annotation/format"
`cleanup`	call `link{cleanup.gds}` if `TRUE`
`verbose`	if `TRUE`, show information

"chromosome": adding or updating two additional nodes '@chrom_rle_val' and '@chrom_rle_len' for faster chromosome indexing, requiring SeqArray>=v1.20.0.

"by.sample": optimizing GDS file for seqApply(..., margin="by.sample"). Warning: optimizing GDS file for reading data by sample may increase file size by up to 2X as genotype data and all format data are duplicated.

None.

Xiuwen Zheng

seqGetData, seqApply

# the file name of VCF
(vcf.fn <- seqExampleFileName("vcf"))
# or vcf.fn <- "C:/YourFolder/Your_VCF_File.vcf"

# convert
seqVCF2GDS(vcf.fn, "tmp.gds", storage.option="ZIP_RA")

# prepare data for the SeqVarTools package
seqOptimize("tmp.gds", target="by.sample")


# list the structure of GDS variables
(f <- seqOpen("tmp.gds"))
# close
seqClose(f)


# delete the temporary file
unlink("tmp.gds")