
markerSampleList
table
of an mlgtResult
.
callGenotypes(resultObject, method = "callGenotypes.default", markerList = names(resultObject@markers), sampleList = resultObject@samples, mapAlleles = FALSE, alleleDb = NULL, approxMatching = FALSE, ...)
mlgtResult
, as returned by
mlgt
variantMap
objects derived from known alleles. As made by
createKnownAlleleList
callGenotypes.default
genotypeCall
). If an
mlgtResult object was supplied then a list of
genotypeCall
objects will be returned, each
named by marker.
mlgt
has generated tables of the most
common variants assigned in each marker/sample pair, an
attempt can be made to call genotypes. This is kept
separate because users might want to try different
calling methods and have the option to map to a known set
of alleles. Currently, only one method is implemented
(`custom'). See
callGenotypes.default
. This function also
includes the option to map variants to a list of known
alleles created using
createKnownAlleleList
. The basic method
makes only perfect matches but a secondary method can be
triggered (approxMatching=TRUE) to find the allele with
the greatest similarity using a local BLAST search.
## Not run:
# data("mlgtResult", package="mlgt")
# my.mlgt.Result
# # the default method
# my.genoytpes <- callGenotypes(my.mlgt.Result)
# # using a custom method
# callGenotypes.custom <- function(table, maxPropUniqueVars=0.5) {
# table$status <- "notCalled"
# table$propUniqueVars <- table$numbVar/table$numbSeq
# table$status <- ifelse(table$propUniqueVars <= maxPropUniqueVars,"good", "bad")
# return(table)
# }
# my.custom.Genotypes <- callGenotypes(my.mlgt.Result, method="callGenotypes.custom")
# ## End(Not run)
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