if (FALSE) {
data("amExample5")
## Produce amDataset object
myDataset <- amDataset(amExample5, missingCode="-99", indexColumn=1,
metaDataColumn=2, ignoreColumn="gender")
## Typical usage
myPairwise <- amPairwise(myDataset, alleleMismatch=2)
## Display analysis as HTML in default browser
summary(myPairwise, html=TRUE)
## Save analysis to HTML file
summary(myPairwise, html="myPairwise.htm")
## Save analysis to CSV file
summary(myPairwise, csv="myPairwise.csv")
## Display analysis as formatted text on the console
summary(myPairwise)
## Compare one dataset against a second
## Both must have same number of allele columns
## Here we create two datasets artificially from one for illustration purposes
myDatasetA <- amDataset(amExample5[sample(nrow(amExample5))[1:25], ],
missingCode="-99", indexColumn=1, ignoreColumn=2)
myDatasetB <- amDataset(amExample5[sample(nrow(amExample5))[1:100], ],
missingCode="-99", indexColumn=1, ignoreColumn=2)
myPairwise2 <- amPairwise(myDatasetA, myDatasetB, alleleMismatch=3)
summary(myPairwise2, html=TRUE)
}
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