recipe bioconductor-buscorrect

Batch Effects Correction with Unknown Subtypes



GPL (>= 2)



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.

package bioconductor-buscorrect

(downloads) docker_bioconductor-buscorrect


1.6.0-0, 1.4.0-0, 1.2.1-0, 1.0.0-0

Required By


With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-buscorrect

and update with:

conda update bioconductor-buscorrect

or use the docker container:

docker pull<tag>

(see bioconductor-buscorrect/tags for valid values for <tag>)