Description Usage Arguments See Also Examples
The function to refine SNPs by resampling and Bayesian inference based on results of globalMPRByMarkers.
1 2 3 4 5 6 7 | 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. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | 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))
|
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