lfa

This is the released version of lfa; for the devel version, see lfa.

Logistic Factor Analysis for Categorical Data

Bioconductor version: Release (3.20)

Logistic Factor Analysis is a method for a PCA analogue on Binomial data via estimation of latent structure in the natural parameter. The main method estimates genetic population structure from genotype data. There are also methods for estimating individual-specific allele frequencies using the population structure. Lastly, a structured Hardy-Weinberg equilibrium (HWE) test is developed, which quantifies the goodness of fit of the genotype data to the estimated population structure, via the estimated individual-specific allele frequencies (all of which generalizes traditional HWE tests).

Author: Wei Hao [aut], Minsun Song [aut], Alejandro Ochoa [aut, cre] , John D. Storey [aut]

Maintainer: Alejandro Ochoa <alejandro.ochoa at duke.edu>

Citation (from within R, enter citation("lfa")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("lfa")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("lfa")

lfa Package	PDF	R Script
Reference Manual	PDF
NEWS	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DimensionReduction, PrincipalComponent, Regression, SNP, Software
Version	2.6.0
In Bioconductor since	BioC 3.2 (R-3.2) (9 years)
License	GPL (>= 3)
Depends	R (>= 4.0)
Imports	utils, methods, corpcor, RSpectra
System Requirements
URL	https://github.com/StoreyLab/lfa
Bug Reports	https://github.com/StoreyLab/lfa/issues

Suggests	knitr, ggplot2, testthat, BEDMatrix, genio
Linking To
Enhances
Depends On Me
Imports Me	gcatest
Suggests Me	jackstraw
Links To Me
Build Report	Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	lfa_2.6.0.tar.gz
Windows Binary (x86_64)	lfa_2.6.0.zip
macOS Binary (x86_64)	lfa_2.6.0.tgz
macOS Binary (arm64)	lfa_2.6.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/lfa
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/lfa
Bioc Package Browser	https://code.bioconductor.org/browse/lfa/
Package Short Url	https://bioconductor.org/packages/lfa/
Package Downloads Report	Download Stats