MPR.genotyping (version 0.8)

globalMPRByMarkers: MPR inference in whole chromosome

Description

The function to do MPR inference in whole chromosome by using localMPR to infer parental genotypes in hundreds of local regions and assemble them aiding with low-coverage sequences of one parent or known markers.

Usage

globalMPRByMarkers(baseData, markers = NULL, alleleA = NULL, numTry = 3,
	numBaseStep = 50, numBaseCandidateStep = numBaseStep * 2,
	numKnownStep = pmax(numBaseStep/5, 10),
	numKnownCandidateStep = numKnownStep * 1.5,
	useMedianToFindKnown = TRUE, maxNStep = 3, scoreMin = 0.8, verbose = FALSE,
	strSTART = "\r", strEND = "", ...)

Arguments

baseData

(Necessary input) character matrix of SNP dataset

markers

character vector of markers data with SNP position names

alleleA

(Necessary input) character vector of one parent allele

numTry

maximum number of the times of using one SNP from one group (or RIL).

numBaseStep

number of SNP to run localMPR().

numBaseCandidateStep

number of SNP candidate in one step

numKnownStep

number of makers to run localMPR().

numKnownCandidateStep

number of makers candidate in one step

useMedianToFindKnown

In one local genomic region (window), we will choose the nearest some makers to this region. Median of the region will be the center.

maxNStep

parameter of localMPR()

scoreMin

be used to control the accuracy of MPR in one local genomic region (one window).

verbose

report verbose progress

strSTART

part of displaying format (verbose)

strEND

part of displaying format (verbose)

…

arguments to be passed to other methods.

See Also

localMPR

Examples

# NOT RUN {
## load sample dataset
data(snpData)
data(markerData)

## select 30 markers randomly
set.seed(123);markers <- sample(names(markerData)[10:50],20)

## select SNP sites which contain the 30 markers
ids <- match(markers,rownames(snpData))
str(myBaseData <- snpData[min(ids):max(ids),])

## global MPR aiding with marker data
allele.MPR <- globalMPRByMarkers(myBaseData,markers=markerData,numTry=3,
			numBaseStep=50,numBaseCandidateStep=100,
            numMarkerStep=10,useMedianToFindKnown=TRUE,
            maxNStep=3,scoreMin=0.8,verbose=TRUE)
# }