DOI: 10.18129/B9.bioc.HDTD    

This is the development version of HDTD; for the stable release version, see HDTD.

Statistical Inference about the Mean Matrix and the Covariance Matrices in High-Dimensional Transposable Data (HDTD)

Bioconductor version: Development (3.7)

Characterization of intra-individual variability using physiologically relevant measurements provides important insights into fundamental biological questions ranging from cell type identity to tumor development. For each individual, the data measurements can be written as a matrix with the different subsamples of the individual recorded in the columns and the different phenotypic units recorded in the rows. Datasets of this type are called high-dimensional transposable data. The HDTD package provides functions for conducting statistical inference for the mean relationship between the row and column variables and for the covariance structure within and between the row and column variables.

Author: Anestis Touloumis [cre, aut], John C. Marioni [aut], Simon Tavar\'{e} [aut]

Maintainer: Anestis Touloumis <A.Touloumis at brighton.ac.uk>

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HTML R Script HDTD to Analyze High-Dimensional Transposable Data
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biocViews DifferentialExpression, GeneExpression, Genetics, Microarray, Sequencing, Software, StatisticalMethod
Version 1.13.3
In Bioconductor since BioC 3.0 (R-3.1) (3.5 years)
License GPL-3
Depends R (>= 3.4)
Imports stats, Rcpp (>= 0.12.13)
LinkingTo Rcpp, RcppArmadillo
Suggests knitr, markdown
URL http://github.com/AnestisTouloumis/HDTD
BugReports http://github.com/AnestisTouloumis/HDTD/issues
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Imports Me
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Source Package HDTD_1.13.3.tar.gz
Windows Binary HDTD_1.13.3.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) HDTD_1.13.3.tgz
Source Repository git clone https://git.bioconductor.org/packages/HDTD
Package Short Url http://bioconductor.org/packages/HDTD/
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