Package: SmartSVA 0.1.3

Jun Chen

SmartSVA: Fast and Robust Surrogate Variable Analysis

Introduces a fast and efficient Surrogate Variable Analysis algorithm that captures variation of unknown sources (batch effects) for high-dimensional data sets. The algorithm is built on the 'irwsva.build' function of the 'sva' package and proposes a revision on it that achieves an order of magnitude faster running time while trading no accuracy loss in return.

Authors:Jun Chen <[email protected]>, Ehsan Behnam <[email protected]>

SmartSVA_0.1.3.tar.gz
SmartSVA_0.1.3.tar.gz(r-4.5-noble)SmartSVA_0.1.3.tar.gz(r-4.4-noble)
SmartSVA_0.1.3.tgz(r-4.4-emscripten)SmartSVA_0.1.3.tgz(r-4.3-emscripten)
SmartSVA.pdf |SmartSVA.html✨
SmartSVA/json (API)

# Install 'SmartSVA' in R:
install.packages('SmartSVA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.33 score 2 packages 36 scripts 291 downloads 11 mentions 1 exports 93 dependencies

Last updated 8 years agofrom:f191d02cbb. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-linux-x86_64OKNov 20 2024

Exports:smartsva.cpp

Dependencies:annotateAnnotationDbiaskpassBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobcachemcliclueclustercodetoolscolorspacecpp11crayoncurlDBIedgeRfansifarverfastICAfastmapformatRfutile.loggerfutile.optionsgenefiltergenericsGenomeInfoDbGenomeInfoDbDataggplot2gluegtablehttrIRangesisobandisvaJADEjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplogrplyrpngqvalueR6RColorBrewerRcppRcppEigenreshape2rlangRSpectraRSQLiteS4VectorsscalessnowstatmodstringistringrsurvivalsvasystibbleUCSC.utilsutf8vctrsviridisLitewithrXMLxtableXVectorzlibbioc