readSNP: Read data in .SNP format

In pievos101/PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses

Read data in .SNP format

Description

This function reads data in .SNP (quality_variant) format, as distributed by the 1001 Genomes project (Arabidopsis).

Usage

readSNP(folder,populations=FALSE,outgroup=FALSE,gffpath=FALSE,
	CHR=FALSE,ref.chr=FALSE,snp.window.size=FALSE,
	parallized=FALSE,ffpackagebool=TRUE,
	include.unknown=FALSE
	)

Arguments

folder	the basepath of the variant_calls
outgroup	vector of outgroup sequences
populations	list of populations
gffpath	the corresponding GFF file
CHR	which chromosome ?, default: all chromosomes
ref.chr	reference chromosome (to classify synonymous/non-synonymous positions)
snp.window.size	scan SNP chunks
parallized	multicore computation
ffpackagebool	use the ff-package to save memory space. (slower)
include.unknown	include positions with unknown nucleotides

Details

The ff-package we use to store the SNP information limits the data size to
individuals * (number of SNPs) <= .Machine$integer.max
The text files containing the SNP information of each individual have to be stored in one folder.
The slots transitions, biallelic.sites, and biallelic.substitutions of the class
"regions.data" will be filled.
At this time, if a GFF/GTF is used the data should be organized in a way that
the "CHR" is a numerical value. The prefix "Chr" or "chr" is also supported.

Value

The function creates an object of class "GENOME"

———————————————————
Following Slots will be filled in the "GENOME" object
———————————————————

	Slot	Description
1.	n.sites	total number of sites
2.	n.biallelic.sites	number of biallelic sites
3.	region.data	some detailed information about the data read
4.	region.names	names of regions

Examples

# GENOME.class <- readSNP("...\SNPData")
# GENOME.class <- readSNP("...\SNPData", CHR=1)
# GENOME.class <- readSNP("...\SNPData", CHR=1, gffpath="Gff_file.gff")
# GENOME.class
# GENOME.class <- neutrality.stats(GENOME.class,FAST=TRUE)
# show the result:
# get.sum.data(GENOME.class)
# [e-mail]

pievos101/PopGenome documentation built on Feb. 24, 2023, 7:11 a.m.