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Batch Effect Removal specifications

Information


Unique identifier OMICS_17094
Name Batch Effect Removal
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python, R
Computer skills Advanced
Stability Stable
Maintained Yes

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No version available

Documentation


Maintainer


  • person_outline Yuval Kluger

Publication for Batch Effect Removal

Batch Effect Removal citation

library_books

Comparability and reproducibility of biomedical data

2012
Brief Bioinform
PMCID: 3713713
PMID: 23193203
DOI: 10.1093/bib/bbs078

[…] specific bias, data pre-processing methods can be used to improve C&R. It is common practice to reduce non-biological sources of variation via pre-processing techniques such as background correction, batch effect removal or normalization. Many of these methods were established during the early days of microarrays at a time when experimental procedures were still being optimized and technical varia […]


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Batch Effect Removal institution(s)
Department of Statistics, Yale University, New Haven, CT, USA; Department of Pathology, Yale School of Medicine, New Haven, CT, USA; Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Applied Mathematics Program, Yale University, New Haven, CT, USA; Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, USA; Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
Batch Effect Removal funding source(s)
Partially funded by NIH grant 1R01HG008383-01A1.

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