{
  "_id": "6a1ae5ef1d7bb097a09f0157",
  "Package": "sva",
  "Title": "Surrogate Variable Analysis",
  "Version": "3.59.0",
  "Author": "Jeffrey T. Leek <jtleek@gmail.com>, W. Evan Johnson\n<wej@bu.edu>, Hilary S. Parker <hiparker@jhsph.edu>, Elana J.\nFertig <ejfertig@jhmi.edu>, Andrew E. Jaffe <ajaffe@jhsph.edu>,\nYuqing Zhang <zhangyuqing.pkusms@gmail.com>, John D. Storey\n<jstorey@princeton.edu>, Leonardo Collado Torres\n<lcolladotor@gmail.com>",
  "Description": "The sva package contains functions for removing batch\neffects and other unwanted variation in high-throughput\nexperiment. Specifically, the sva package contains functions\nfor the identifying and building surrogate variables for\nhigh-dimensional data sets. Surrogate variables are covariates\nconstructed directly from high-dimensional data (like gene\nexpression/RNA sequencing/methylation/brain imaging data) that\ncan be used in subsequent analyses to adjust for unknown,\nunmodeled, or latent sources of noise. The sva package can be\nused to remove artifacts in three ways: (1) identifying and\nestimating surrogate variables for unknown sources of variation\nin high-throughput experiments (Leek and Storey 2007 PLoS\nGenetics,2008 PNAS), (2) directly removing known batch effects\nusing ComBat (Johnson et al. 2007 Biostatistics) and (3)\nremoving batch effects with known control probes (Leek 2014\nbiorXiv). Removing batch effects and using surrogate variables\nin differential expression analysis have been shown to reduce\ndependence, stabilize error rate estimates, and improve\nreproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008\nPNAS or Leek et al. 2011 Nat. Reviews Genetics).",
  "Maintainer": "Jeffrey T. Leek <jtleek@gmail.com>, John D. Storey\n<jstorey@princeton.edu>, W. Evan Johnson <wej@bu.edu>",
  "License": "Artistic-2.0",
  "biocViews": "ImmunoOncology, Microarray, StatisticalMethod,\nPreprocessing, MultipleComparison, Sequencing, RNASeq,\nBatchEffect, Normalization",
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2025-10-29 14:09:21 UTC",
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