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slfm

Fitting a Bayesian Sparse Latent Factor Model in Gene Expression Analysis

v1.0.2 · Nov 28, 2023 · GPL-2

Description

Set of tools to find coherent patterns in gene expression (microarray) data using a Bayesian Sparse Latent Factor Model (SLFM) <DOI:10.1007/978-3-319-12454-4_15>. Considerable effort has been put to build a fast and memory efficient package, which makes this proposal an interesting and computationally convenient alternative to study patterns of gene expressions exhibited in matrices. The package contains the implementation of two versions of the model based on different mixture priors for the loadings: one relies on a degenerate component at zero and the other uses a small variance normal distribution for the spike part of the mixture.

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r-devel-windows-x86_64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies Rcpp coda lattice slfm

Version History

new 1.0.2 Mar 10, 2026
updated 1.0.2 ← 1.0.1 diff Nov 27, 2023
updated 1.0.1 ← 1.0.0 diff Mar 14, 2020
updated 1.0.0 ← 0.2.3 diff Jul 27, 2019
updated 0.2.3 ← 0.2.2 diff May 26, 2019
updated 0.2.2 ← 0.2.1 diff Aug 9, 2015
updated 0.2.1 ← 0.2.0 diff Aug 7, 2015
updated 0.2.0 ← 0.1 diff Jul 28, 2015
new 0.1 May 7, 2014