| bed_fastJaccardEVs {locStra} | R Documentation |
Computation of the k leading eigenvectors of the Jaccard similarity matrix directly from a bed+bim+fam file.. Note that this computation is only approximate and does not necessarily coincide with the result obtained by extracting the k leading eigenvectors of the Jaccard matrix computed with the function jaccardMatrix.
Description
Computation of the k leading eigenvectors of the Jaccard similarity matrix directly from a bed+bim+fam file.. Note that this computation is only approximate and does not necessarily coincide with the result obtained by extracting the k leading eigenvectors of the Jaccard matrix computed with the function jaccardMatrix.
Usage
bed_fastJaccardEVs(f, k, q = 2)
Arguments
f |
The filename of the bed file (including its extension). The bim and fam files need to be in the same folder and have the same base filename. |
k |
The number of leading eigenvectors. |
q |
The number of power iteration steps (default is |
Value
The k leading eigenvectors of the Jaccard matrix of m as a column matrix.
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.
N. Halko, P.G. Martinsson, and J.A. Tropp (2011). Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions. SIAM Review: 53(2), pp. 217–288.
F. Prive, M. Blum, H. Aschard, B.J. Vilhjalmsson (2022). bigsnpr: Analysis of Massive SNP Arrays. https://cran.r-project.org/package=bigsnpr
Examples
require(locStra)