recipe bioconductor-lfa

Logistic Factor Analysis for Categorical Data



GPL (>= 3)




biotools: lfa, doi: 10.1093/bioinformatics/btv641

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).

package bioconductor-lfa

(downloads) docker_bioconductor-lfa



depends libblas:


depends libgcc-ng:


depends liblapack:


depends r-base:


depends r-corpcor:

depends r-rspectra:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-lfa

and update with::

   mamba update bioconductor-lfa

To create a new environment, run:

mamba create --name myenvname bioconductor-lfa

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-lfa/tags`_ for valid values for ``<tag>``)

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