Package 'haplotyper'

Title: Tool for Clustering Genotypes in Haplotypes
Description: Function to identify haplotypes within QTL (Quantitative Trait Loci). One haplotype is a combination of SNP (Single Nucleotide Polymorphisms) within the QTL. This function groups together all individuals of a population with the same haplotype. Each group contains individual with the same allele in each SNP, whether or not missing data. Thus, haplotyper groups individuals, that to be imputed, have a non-zero probability of having the same alleles in the entire sequence of SNP's. Moreover, haplotyper calculates such probability from relative frequencies.
Authors: Sebastian Simondi <[email protected]> and Gaston Quero, with contributions from Victoria Bonnecarrere and Lucia Gutierrez
Maintainer: Gaston Quero <[email protected]>
License: GPL-3
Version: 0.1
Built: 2025-02-13 05:28:49 UTC
Source: https://github.com/cran/haplotyper

Help Index


haplotyper function identifies haplotypes within QTL.

Description

This function groups together all individuals of a population with the same haplotype.

Usage

haplotyper(x, Print = FALSE)

Arguments

x

a data.frame that should be loaded with read.table function. Each row represents the individuals while each column represents the markers. The first column contains the names of the genotypes.

Print

option for print the haplotyper result. The default is FALSE

Details

Each group contains individual with the same allele in each SNP, whether or not missing data.

Value

a matrix with the haplotypes

Author(s)

Sebastian Simondi, Victoria Bonnecarrere, Lucia Gutierrez, Gaston Quero

See Also

read.table function

Examples

## Not run: 
data(rice_qtl)
haplotyper(rice_qtl)

## End(Not run)

Real experimental data

Description

The data is a QTL for rice Grain Quality

Usage

rice_qtl

Format

A data frame 326 rows (individual) and 38 variables (SNPs)

Source

Uruguayan Rice Breeding GWAS (URiB)


simple QTL simulated

Description

A dataset containing the marcadores

Usage

sim_qtl

Format

A data frame 5 rows (individuals) and 7 variables (snps)

Source

simulated data