BigDataStatMeth: Statistical Methods and Algorithms for Big Data

Basic Algebra methods using parallel algorithms to be used in big data problems such as omics data analyses. The functions will consider as input an HDF5 data file, an object of class DelayedArray or an R object.

Version: 0.99.32
Depends: R (≥ 3.6.0)
Imports: data.table, Rcpp (≥ 1.0.6), RcppParallel (≥ 5.0.2), RCurl, rhdf5, utils
LinkingTo: Rcpp, RcppEigen, RcppParallel, beachmat, Rhdf5lib, RSpectra, BH
Suggests: HDF5Array, DelayedArray, Matrix, BiocStyle, knitr, rmarkdown, ggplot2, microbenchmark
Published: 2022-03-29
Author: Dolors Pelegri-Siso ORCID iD [aut, cre], Juan R. Gonzalez ORCID iD [aut]
Maintainer: Dolors Pelegri-Siso <dolors.pelegri at isglobal.org>
License: MIT + file LICENSE
NeedsCompilation: yes
SystemRequirements: GNU make, C++11
Materials: README
CRAN checks: BigDataStatMeth results

Documentation:

Reference manual: BigDataStatMeth.pdf
Vignettes: Algebra and Statistical Methods for Big Data witn HDF5 files
Algebra and Statistical Methods for Big Data with Bioconductor

Downloads:

Package source: BigDataStatMeth_0.99.32.tar.gz
Windows binaries: r-devel: BigDataStatMeth_0.99.32.zip, r-release: BigDataStatMeth_0.99.32.zip, r-oldrel: BigDataStatMeth_0.99.32.zip
macOS binaries: r-release (arm64): BigDataStatMeth_0.99.32.tgz, r-release (x86_64): BigDataStatMeth_0.99.32.tgz, r-oldrel: BigDataStatMeth_0.99.32.tgz
Old sources: BigDataStatMeth archive

Linking:

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