alleleSharing: allele sharing based on ibs
In molepi/omicsPrint: Cross omic genetic fingerprinting

Description Usage Arguments Details Value Author(s) Examples

Run the allele sharing algorithm based on ibs

alleleSharing(x, y = NULL, relations = NULL, idx.col = "idx",
  idy.col = "idy", rel.col = "relation_type", callRate = 0.95,
  coverageRate = 2/3, alpha = 0, maf = 0, alignment = FALSE,
  assayNameX = NULL, assayNameY = NULL, verbose = TRUE)

`x, y`	genotype matrix with row and column names; if this is a SummarizedExperiment or a MultiAssayExperiment assayName must also be specified
`relations`	'data.frame' with relations and their mapping identifiers, provide columns if different from the default and beware identifiers should match with colnames of x and y
`idx.col`	column name containing mapping identifiers
`idy.col`	column name containing mapping identifiers
`rel.col`	column name containing the relations, i.e. identical, parentoffspring, etc.
`callRate`	default 0.95 SNPs that are called in less then the threshold are dropped
`coverageRate`	default 2/3 samples with less then threshold SNPs called are set to NA
`alpha`	significance level for Hardy-Weinberg test default alpha = 0, no filtering, internaly Bonferonni multiple testing will be applied
`maf`	minor allele frequency threshold, variants with lower frequency (default 0 no filtering) will be dropped
`alignment`	default FALSE
`assayNameX`	the name of the assay to be used for x (see x, y)
`assayNameY`	same as assayNameX, but for y; if y is not specified, the assay will be retreived from x
`verbose`	show progress default TRUE

calculate mean and variance of identity by state between genotypes, coded as 1,2,3, of all sample pairs either give one omic inferred set of SNPs or two from different omic types.

'Strand Alignment' is required if methylation data inferred genotypes are compared with DNA based genotypes, i.e., DNA based genotype is 3 whereas methylation is 1. The strand alignment step will fix this.

Notice that there are two algorithms for calculating allele sharing. One for the case one matrix is provided and one for the case two, x and y, are provided. If one is provided the algorithm takes in account the symmetric relations between pairs i.e. x12 = x21 etc.

To improve the lookup of relations, which can be millions of say 1000 samples are provided, a hash-table is created from the provided data.frame with relations.

data.frame with mean and variance ibs between all pairs

mvaniterson

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)