localMPR: infer parental genotypes by minimizing the number of...

Description Usage Arguments Details Value See Also Examples

Description

The core function to infer parental genotypes (MPR inference) in a local chromosome region by minimizing the number of recombination events in the population.

Usage

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localMPR(baseData, allele.matrix = NULL, maxNStep = 5,
	returnNumRecomEvents = FALSE, verbose = FALSE, strEND = "\n", ...)

Arguments

baseData

a character matrix of SNP

allele.matrix

a character matrix of alleles

returnNumRecomEvents

whether report the number of recombination events in the final result

maxNStep

the number of SNP in an exchange of the alleles.

verbose

report verbose progress.

strEND

the part of displaying format (verbose)

...

arguments to be passed to other methods.

Details

Several factors may affect the accuracy of MPR inference: (a). The number of SNPs processed each time (window size); (b). The density of putative SNPs (the distance between SNP sites); (c). The maximum step size of the heuristic perturbation (the parameter of maxNStep); (d). The number of RILs. And we wrote core code in C to improve computational speed.

Value

the result of local MPR genotyping allele

See Also

NumRecomEvents,globalMPRByMarkers,globalMPRRefine,

Examples

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set.seed(123)
## select 50 SNP sites to test inference of parental genotypes from snpData.rda
data(myBaseData)

## random assignments of parental genotypes to alleles will result in
## a big number of recombinations 
allele.random <- base2Allele(myBaseData)

## a big number of recombinations
NumRecomEvents(myBaseData,allele.random)
## 162

## MPR inference with maximum step size of 5
allele.MPR <- localMPR(baseData=myBaseData,maxIterate=50,maxNStep=5,showDetail=TRUE)

## should be a small number compared with random assignments above 
NumRecomEvents(myBaseData,allele.MPR)
## 33

MPR.genotyping documentation built on May 2, 2019, 3:26 a.m.