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sva | Capturing heterogeneity in gene expression studies

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Allows to remove batch effects and other unwanted variation in high-throughput experiment. SVA is a package containing several functions permitting to identify and build surrogate variables for large data sets. Artifacts can be removed in three ways: (i) identification and estimation of surrogate variables, (ii) direct removal of known batch effect with ComBat and (iii) removal of batch effect with known probes.

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sva classification

sva specifications

Unique identifier:
OMICS_00861
Alternative name:
fSVA
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
License:
Artistic License version 2.0
Version:
3.24.4
Requirements:
mgcv, genefilter, BiocParallel
Name:
Surrogate Variable Analysis
Software type:
Package/Module
Restrictions to use:
None
Programming languages:
R
Computer skills:
Advanced
Stability:
Stable
Maintained:
Yes

Subtools

  • qSVA
  • fSVA

sva distribution

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sva support

Documentation

Maintainers

  • Jeffrey Leek <>
  • John D. Storey <>
  • W. Evan Johnson <>
  • Andrew E. Jaffe <>

Credits

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Publications

Institution(s)

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Center for Bioinformatics and Computational Biology, Department of Computer Science, University of Maryland, College Park, MD, USA

Funding source(s)

Supported by NIH (R01GM105705 and R01GM103552) and by a Bloomberg Fellowship.

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