Bioconductor Developer Survey 2026 Now Open!

MetaDICT

Microbiome data integration method via shared dictionary learning

Bioconductor version: 3.24 · Package version: 1.3.0

Other Bioconductor versions

devel is the development version; release is the current stable one.

3.24 (devel), 3.23 (release)

MetaDICT is a method for the integration of microbiome data. This method is designed to remove batch effects and preserve biological variation while integrating heterogeneous datasets. MetaDICT can better avoid overcorrection when unobserved confounding variables are present.

DOI: 10.18129/B9.bioc.MetaDICT

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("MetaDICT")

Details

MaintainerBo Yuan <boyuan5@illinois.edu>
AuthorBo Yuan [aut, cre] (ORCID: <https://orcid.org/0009-0008-5428-4447>), Shulei Wang [aut]
LicenseArtistic-2.0
URLhttps://github.com/BoYuan07/MetaDICT
Bug Reportshttps://github.com/BoYuan07/MetaDICT/issues
Source branchdevel
Build report Bioconductor build system, r-universe
biocViewsBatchEffect, Clustering, Microbiome, Sequencing, Software
Package Short Url https://bioconductor.org/packages/MetaDICT/

Citation

From within R, enter citation("MetaDICT"):

Bo Yuan, Shulei Wang. MetaDICT: Microbiome data integration method via shared dictionary learning. doi:10.18129/B9.bioc.MetaDICT, R package version 1.3.0, https://bioconductor.org/packages/MetaDICT.

Generated from the package metadata; it may differ from the package's own citation.

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageMetaDICT_1.3.0.tar.gz
Windows binary (x86_64)MetaDICT_1.3.0.zip
macOS binary (arm64)MetaDICT_1.3.0.tgz
macOS binary (x86_64)MetaDICT_1.3.0.tgz
Dependencies

Depends: R (>= 4.2.0)

Imports: stats, RANN, igraph, vegan, edgeR, ecodist, ggplot2, viridis, ggpubr, ape, cluster, matrixStats

Suggests: BiocStyle, knitr, rmarkdown, DT, ggraph, tidyverse, testthat (>= 3.0.0)