Import excel files into R. Supports '.xls' via the
    embedded 'libxls' C library <https://github.com/libxls/libxls> and
    '.xlsx' via the embedded 'RapidXML' C++ library
    <http://rapidxml.sourceforge.net>.  Works on Windows, Mac and Linux
    without external dependencies.

cellranger, Rcpp (>= 0.12.18), tibble (>= 1.3.1), utils

covr, knitr, rmarkdown, rprojroot (>= 1.1), testthat

Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>),
  Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>),
  RStudio [cph, fnd] (Copyright holder of all R code and all C/C++ code
    without explicit copyright attribution),
  Marcin Kalicinski [ctb, cph] (Author of included RapidXML code),
  Komarov Valery [ctb, cph] (Author of included libxls code),
  Christophe Leitienne [ctb, cph] (Author of included libxls code),
  Bob Colbert [ctb, cph] (Author of included libxls code),
  David Hoerl [ctb, cph] (Author of included libxls code),
  Evan Miller [ctb, cph] (Author of included libxls code)

Analysis of Large-Scale Pharmacogenomic Data

Petr Smirnov, Zhaleh Safikhani, Mark Freeman, Benjamin Haibe-Kains

Contains a set of functions to perform large-scale analysis of pharmacogenomic data.

Biobase, piano, magicaxis, RColorBrewer, parallel, caTools,
methods, downloader, stats, utils, graphics, grDevices, lsa,
reshape2

GeneExpression, Pharmacogenetics, Pharmacogenomics,
Software, Classification

Access the Bioconductor Project Package Repository

A convenient tool to install and update Bioconductor packages.

c(
    person("Martin", "Morgan", email = "martin.morgan@roswellpark.org",
        role = "aut", comment = c(ORCID = "0000-0002-5874-8148")),
    person("Marcel", "Ramos", email = "marcel.ramos@roswellpark.org",
        role = c("ctb", "cre"), comment = c(ORCID = "0000-0002-3242-0582")))

BiocStyle, BiocVersion, remotes, testthat, knitr, withr

The basic idea of latent semantic analysis (LSA) is, 
  that text do have a higher order (=latent semantic) structure which, 
  however, is obscured by word usage (e.g. through the use of synonyms 
  or polysemy). By using conceptual indices that are derived statistically 
  via a truncated singular value decomposition (a two-mode factor analysis) 
  over a given document-term matrix, this variability problem can be overcome.