Highthroughput 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 BatcheffectscorrectionwithUnknownSubtypes 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 linearorder computation complexity.
Package details 


Author  Xiangyu Luo <[email protected]>, Yingying Wei <[email protected]> 
Bioconductor views  BatchEffect Bayesian Clustering FeatureExtraction GeneExpression StatisticalMethod 
Maintainer  Xiangyu Luo <[email protected]> 
License  GPL (>= 2) 
Version  0.99.8 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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