Package: lfa Title: Logistic Factor Analysis for Categorical Data Version: 2.12.0 Authors@R: c( person(given = "Wei", family = "Hao", role = "aut", email = "whao@princeton.edu"), person(given = "Minsun", family = "Song", role = "aut"), person(given = "Alejandro", family = "Ochoa", role = c("aut", "cre"), email = "alejandro.ochoa@duke.edu", comment = c(ORCID = "0000-0003-4928-3403")), person(given = "John D.", family = "Storey", role = "aut", email = "jstorey@princeton.edu", comment = c(ORCID = "0000-0001-5992-402X")) ) Encoding: UTF-8 LazyData: true Description: 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). Imports: methods, corpcor, RSpectra, BEDMatrix, genio Depends: R (>= 4.0) Suggests: knitr, rmarkdown, ggplot2, testthat VignetteBuilder: knitr License: GPL (>= 3) biocViews: SNP, DimensionReduction, PrincipalComponent, Regression BugReports: https://github.com/StoreyLab/lfa/issues URL: https://github.com/StoreyLab/lfa Roxygen: list(markdown = TRUE) RoxygenNote: 7.3.3 Config/pak/sysreqs: libx11-dev Repository: Bioconductor 3.23 Date/Publication: 2026-04-28 13:00:58 UTC RemoteUrl: https://github.com/bioc/lfa RemoteRef: RELEASE_3_23 RemoteSha: 1c0bf78169363e7bb4b06a62142d61525f45d0a8 NeedsCompilation: yes Packaged: 2026-09-29 09:56:05 UTC; root Author: Wei Hao [aut], Minsun Song [aut], Alejandro Ochoa [aut, cre] (ORCID: ), John D. Storey [aut] (ORCID: ) Maintainer: Alejandro Ochoa