XiangyuLuo/BUScorrect: Batch Effects Correction with Unknown Subtypes

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.

Getting started

Package details

AuthorXiangyu Luo <[email protected]>, Yingying Wei <[email protected]>
Bioconductor views BatchEffect Bayesian Clustering FeatureExtraction GeneExpression StatisticalMethod
MaintainerXiangyu Luo <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
XiangyuLuo/BUScorrect documentation built on June 14, 2019, 3:31 p.m.