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BUScorrect

Batch Effects Correction with Unknown Subtypes

Bioconductor version: 3.24 · Package version: 1.31.0

High-throughput experimental data are accumulating exponentially in public databases. However, mining valid scientific discoveries from these abundant resources is hampered by technical artifacts and inherent biological heterogeneity. The former are usually termed "batch effects," and the latter is often modelled by "subtypes." The R package BUScorrect fits a Bayesian hierarchical model, the Batch-effects-correction-with-Unknown-Subtypes model (BUS), to correct batch effects in the presence of unknown subtypes. BUS is capable of (a) correcting batch effects explicitly, (b) grouping samples that share similar characteristics into subtypes, (c) identifying features that distinguish subtypes, and (d) enjoying a linear-order computation complexity.

Installation

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

BiocManager::install("BUScorrect")

Details

MaintainerXiangyu Luo <xyluo1991@gmail.com>
AuthorXiangyu Luo <xyluo1991@gmail.com>, Yingying Wei <yweicuhk@gmail.com>
LicenseGPL (>= 2)
Downloads rank476
Source branchdevel
biocViewsBatchEffect, Bayesian, Clustering, FeatureExtraction, GeneExpression, Software, StatisticalMethod

Download

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

Source packageBUScorrect_1.31.0.tar.gz
Windows binary (x86_64)BUScorrect_1.31.0.zip
macOS binary (arm64)BUScorrect_1.31.0.tgz
macOS binary (x86_64)BUScorrect_1.31.0.tgz
Dependencies

Depends: R (>= 3.5.0)

Imports: gplots, methods, grDevices, stats, SummarizedExperiment

Suggests: BiocStyle, knitr, RUnit, BiocGenerics