Package: BClustLonG 0.1.3

BClustLonG: A Dirichlet Process Mixture Model for Clustering Longitudinal Gene Expression Data

Many clustering methods have been proposed, but most of them cannot work for longitudinal gene expression data. 'BClustLonG' is a package that allows us to perform clustering analysis for longitudinal gene expression data. It adopts a linear-mixed effects framework to model the trajectory of genes over time, while clustering is jointly conducted based on the regression coefficients obtained from all genes. To account for the correlations among genes and alleviate the high dimensionality challenges, factor analysis models are adopted for the regression coefficients. The Dirichlet process prior distribution is utilized for the means of the regression coefficients to induce clustering. This package allows users to specify which variables to use for clustering (intercepts or slopes or both) and whether a factor analysis model is desired. More details about this method can be found in Jiehuan Sun, et al. (2017) <doi:10.1002/sim.7374>.

Authors:Jiehuan Sun [aut, cre], Jose D. Herazo-Maya[aut], Naftali Kaminski[aut], Hongyu Zhao [aut], and Joshua L. Warren [aut],

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BClustLonG/json (API)

# Install 'BClustLonG' in R:
install.packages('BClustLonG', repos = c('https://jjr1234.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • data - Simulated dataset for testing the algorithm

On CRAN:

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

2 exports 0.36 score 13 dependencies 1 mentions 3 scripts 247 downloads

Last updated 4 years agofrom:088916fda0. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 15 2024
R-4.5-win-x86_64WARNINGSep 15 2024
R-4.5-linux-x86_64WARNINGSep 15 2024
R-4.4-win-x86_64WARNINGSep 15 2024
R-4.4-mac-x86_64WARNINGSep 15 2024
R-4.4-mac-aarch64WARNINGSep 15 2024
R-4.3-win-x86_64WARNINGSep 15 2024
R-4.3-mac-x86_64WARNINGSep 15 2024
R-4.3-mac-aarch64WARNINGSep 15 2024

Exports:BClustLonGcalSim

Dependencies:bootlatticelme4lpSolveMASSMatrixmcclustminqanlmenloptrRcppRcppArmadilloRcppEigen

The BClustLonG Package: A Dirichlet Process Mixture Model for Clustering Longitudinal Gene Expression Data

| Jiehuan Sun$^1$, Jose D. Herazo-Maya$^2$, Naftali Kaminski$^2$, Hongyu Zhao$^1$, and Joshua L. Warren$^1$ | $^1$Department of Biostatistics, Yale School of Public Health | $^2$Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine

Rendered fromBClustLonG.Rmdusingknitr::rmarkdownon Sep 15 2024.

Last update: 2017-12-15
Started: 2017-12-15