Package: slfm 1.0.2

Vinicius Mayrink

slfm: Fitting a Bayesian Sparse Latent Factor Model in Gene Expression Analysis

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.

Authors:Vinicius Mayrink [aut, cre], Joao Duarte [aut]

slfm_1.0.2.tar.gz
slfm_1.0.2.tar.gz(r-4.5-noble)slfm_1.0.2.tar.gz(r-4.4-noble)
slfm_1.0.2.tgz(r-4.4-emscripten)slfm_1.0.2.tgz(r-4.3-emscripten)
slfm.pdf |slfm.html✨
slfm/json (API)
NEWS

# Install 'slfm' in R:
install.packages('slfm', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.00 score 209 downloads 4 exports 4 dependencies

Last updated 1 years agofrom:ed34066e57. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 23 2025
R-4.5-linux-x86_64OKMar 23 2025
R-4.4-linux-x86_64OKMar 23 2025

Exports:plot_matrixprocess_matrixslfmslfm_list

Dependencies:codalatticeRcppRcppArmadillo

Citation

To cite slfm in publications use:

Duarte JDN, Mayrink VD (2019). “slfm: An R Package to Evaluate Coherent Patterns in Microarray Data via Factor Analysis.” Journal of Statistical Software, 90(9), 1–22. doi:10.18637/jss.v090.i09.

Corresponding BibTeX entry: 

  @Article{,
    title = {{slfm}: An {R} Package to Evaluate Coherent Patterns in
      Microarray Data via Factor Analysis},
    author = {Joao Daniel N. Duarte and Vinicius D. Mayrink},
    journal = {Journal of Statistical Software},
    year = {2019},
    volume = {90},
    number = {9},
    pages = {1--22},
    doi = {10.18637/jss.v090.i09},
  }