globalMPRRefine: refine SNPs by resampling
In MPR.genotyping: Maximum Parsimony of Recombination to Infer Parental Genotypes

Description Usage Arguments See Also Examples

The function to refine SNPs by resampling and Bayesian inference based on results of globalMPRByMarkers.

globalMPRRefine(baseData, markers = NULL, alleleA = NULL, numGroup = ncol(baseData), 
	groupSort = FALSE, numPerm = 10, numTry = 3, numBaseStep = 50, 
	numBaseCandidateStep = numBaseStep * 2, numKnownStep = numBaseStep/2, 
	numKnownCandidateStep = numBaseStep * 2, useMedianToFindKnown = TRUE, 
	maxNStep = 3, scoreMin = 0.8, useOnlyKnownToType = FALSE, useBayes = FALSE, 
	errorRate = 5e-04, saveMidData = FALSE, verbose = FALSE, strSTART = "\r", 
	strEND = "", ...)

`baseData`	Your SNP matrix
`markers`	Your markers data
`alleleA`	We can use the results of globalMPRByMarkers() to be something like markers
`numGroup`	The number of group to run in one permutation.
`groupSort`	Your groups (or RILs) will sort by coverage.(higher coverage will make the result in local region better)
`numPerm`	The number of permutations
`numTry`	The maximum number of the times of using one SNP from one group (or RIL).
`numBaseStep`	The number of SNP to run localMPR().
`numBaseCandidateStep`	The number of SNP candidate in one step
`numKnownStep`	The number of makers to run localMPR().
`numKnownCandidateStep`	The 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`	The parameter of localMPR()
`scoreMin`	The score is used to control the accuracy of MPR in one local genomic region (window).
`useOnlyKnownToType`	Using different scoring system
`useBayes`	"useBayes=TRUE" will make this routine integrate with Bayesian inference
`errorRate`	the parameter of genotypeCallsBayes() if you set "useBayes=TRUE".
`saveMidData`	If you want to check the effect of the number of permutations, "saveMidData = TRUE" will help you.
`verbose`	Report verbose progress.
`strSTART`	The part of displaying format (verbose)
`strEND`	The part of displaying format (verbose)
`...`	Arguments to be passed to other methods.

globalMPRByMarkers

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)
			 
## then you need to refine the MPR results
set.seed(123);system.time(all.res <- globalMPRRefine(myBaseData,alleleA=na.omit(
            allele.MPR[,1]),numGroup=238,groupSort=TRUE,numPerm=1,numTry=3,
            numBaseStep=50,numBaseCandidateStep=100,numKnownStep=30,
            numKnownCandidateStep=50,useMedianToFindKnown=TRUE,
            maxNStep=3,scoreMin=0.8,saveMidData=TRUE,verbose=TRUE))