jaccardMatrix: C++ implementation to compute the Jaccard similarity matrix...

In locStra: Fast Implementation of (Local) Population Stratification Methods

C++ implementation to compute the Jaccard similarity matrix for a (sparse) input matrix.

Description

C++ implementation to compute the Jaccard similarity matrix for a (sparse) input matrix.

Usage

jaccardMatrix(m, useCpp = TRUE, sparse = TRUE)

Arguments

m	A (sparse) matrix for which the Jaccard similarity matrix is sought. The input matrix is assumed to be oriented to contain the data for one individual per column.
useCpp	Flag to switch between R or C++ implementations. Default is useCpp=TRUE.
sparse	Flag to switch between purpose-built dense or sparse implementations. Default is sparse=TRUE.

Value

The Jaccard matrix of m.

References

Dmitry Prokopenko, Julian Hecker, Edwin Silverman, Marcello Pagano, Markus Noethen, Christian Dina, Christoph Lange and Heide Fier (2016). Utilizing the Jaccard index to reveal population stratification in sequencing data: a simulation study and an application to the 1000 Genomes Project. Bioinformatics, 32(9):1366-1372.

Examples

require(locStra)
require(Matrix)
m <- matrix(sample(0:1,15,replace=TRUE),ncol=3)
sparseM <- Matrix(m,sparse=TRUE)
print(jaccardMatrix(sparseM))

locStra documentation built on April 13, 2022, 1:07 a.m.