fsimpute: Impute genotypes in bi-parental populations of finite selfing

Description Usage Arguments Value

View source: R/fsimpute.R

Description

Imputes missing genotype data using conditional genotype probabilities derived from a Hidden Markov Model. Founder genotypes are then imputed from the conditional genotype probabilities in the progeny. Then progeny genotypes are imputed using the imputed founder genotypes.

Usage

1
2
3
fsimpute(cross, prob.threshold = 0.7, type = "discrete", step = 0,
  off.end = 0, error.prob = 1e-04, map.function = c("haldane", "kosambi",
  "c-f", "morgan"), stepwidth = c("fixed", "variable", "max"))

Arguments

cross

An object of class cross from the package read.cross. This object should be generated using the function prep_cross.

prob.threshold

The minimum conditional genotype probability to declare a site as having been inherited from a certain parent.

type

The genotype output type. Can be discrete to code each imputed genotype as the most likely genotype, or continuous to code each imputed genotype as a weighted average based on the genotype probabilities.

step

See calc.genoprob.

off.end

See calc.genoprob.

error.prob

See calc.genoprob.

stepwidth

See calc.genoprob.

map.functions

See calc.genoprob.

Value

The cross object is returned with the additional item imputed, which contains the following information:

$stats

Some measures on the imputed genotypes, including the proportion of missing data

$founders

The imputed founder genotypes

$finals

The imputed progeny genotypes


neyhartj/fsimpute documentation built on May 23, 2019, 4:29 p.m.