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slfm  

Fitting a Bayesian Sparse Latent Factor Model in Gene Expression Analysis
View on CRAN: Click here


Download and install slfm package within the R console
Install from CRAN:
install.packages("slfm")

Install from Github:
library("remotes")
install_github("cran/slfm")

Install by package version:
library("remotes")
install_version("slfm", "1.0.2")



Attach the package and use:
library("slfm")
Maintained by
Vinicius Mayrink
[Scholar Profile | Author Map]
First Published: 2014-05-08
Latest Update: 2020-03-15
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.
How to cite:
Vinicius Mayrink (2014). slfm: Fitting a Bayesian Sparse Latent Factor Model in Gene Expression Analysis. R package version 1.0.2, https://cran.r-project.org/web/packages/slfm. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1 (2014-05-08 15:00), 0.2.0 (2015-07-29 06:21), 0.2.1 (2015-08-08 17:41), 0.2.2 (2015-08-10 09:10), 0.2.3 (2019-05-27 14:50), 1.0.0 (2019-07-28 01:00), 1.0.1 (2020-03-15 23:20)
Other packages that cited slfm R package
View slfm citation profile
Other R packages that slfm depends, imports, suggests or enhances
Complete documentation for slfm
Functions, R codes and Examples using the slfm R package
Some associated functions: plot_matrix . print.slfm . process_matrix . slfm . slfm_list . slfm_package . 
Some associated R codes: RcppExports.R .  Full slfm package functions and examples
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