fitSnpNmf: Non-negative matrix factorization (NMF) of a matrix...

View source: R/fitSnpNmf.R

fitSnpNmfR Documentation

Non-negative matrix factorization (NMF) of a matrix containing SNP probe signals

Description

Non-negative matrix factorization (NMF) of a matrix containing SNP probe signals.

Usage

fitSnpNmf(V, acc=0.02, maxIter=10, maxIterRlm=20, refs=NULL)

Arguments

V

An KxI matrix where I is the number of arrays and K is the number of probe where K should be even (K=2L).

acc

A positive double specifying the converence threshold. For more details on convergence, see below.

maxIter

A positive integer specifying the maximum number of iterations used to calculate the decomposition.

maxIterRlm

A positive integer specifying the maximum number of iterations used in rlm.

refs

An index vector (integer or logical) specifying the reference samples. If NULL, all samples are used as a reference.

Details

The algorithm is considered to have converged when the maximum update of any allele-specific copy number of any array (H) is greater than acc.

Value

Returns a list:

W

The Kx2 matrix containing allele-specific affinity estimates.

H

A 2xI matrix containing allele-specific copy number estimates.

hasConverged

TRUE if the algorithm converged, otherwise FALSE. If not applicable, it is NA.

nbrOfIterations

The number of iteration ran before stopping. If not applicable, it is NA.

See Also

WHInit(), robustWInit(), robustHInit(), and removeOutliers().


ACNE documentation built on May 29, 2024, 12:33 p.m.