inferRelations: predict mismatches

In molepi/omicsPrint: Cross omic genetic fingerprinting

Description

predict mismatches

Usage

inferRelations(data, n = 100, plot.it = TRUE, verbose = FALSE, ...)

Arguments

data	output from allelesharing
n	= 100 default interpolation for showing the classification boundaries
plot.it	= TRUE default plot classification graph and returing mismatches otherwise return all
verbose	default FALSE, if TRUE show confusion matrix
...	optional plotting argument passed to plot

Details

based on all data a classifier is build using Linear Discriminant Analysis and on the same data a prediction is performed in order to detect wrong sample relationships. The assumption is that the majority of sample relations is correct otherwise we could not do this!

Value

predicted mismatches

Author(s)

mvaniterson

Examples

set.seed(12345)
beta <- matrix(runif(100*10, 0,1), nrow=100)
beta[1:5, 1:5]
colnames(beta) <- paste0("sample", 1:10)
genotype <- beta2genotype(beta)
genotype[1:5, 1:5]
data <- alleleSharing(genotype)
head(data)
inferRelations(data)

molepi/omicsPrint documentation built on May 23, 2019, 6:02 a.m.