To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R") biocLite("HDTD")
In most cases, you don't need to download the package archive at all.
Bioconductor version: 3.0
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, John C. Marioni and Simon Tavare
Maintainer: Anestis Touloumis <Anestis.Touloumis at cruk.cam.ac.uk>
Citation (from within R,
enter citation("HDTD")
):
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R") biocLite("HDTD")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("HDTD")
R Script | HDTD to Analyze High-Dimensional Transposable Data | |
Reference Manual | ||
Text | NEWS |
biocViews | DifferentialExpression, GeneExpression, Genetics, Microarray, RNASeq, Software, StatisticalMethod |
Version | 1.0.0 |
In Bioconductor since | BioC 3.0 (R-3.1) |
License | GPL-3 |
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Build Report |
Follow Installation instructions to use this package in your R session.
Package Source | HDTD_1.0.0.tar.gz |
Windows Binary | HDTD_1.0.0.zip |
Mac OS X 10.6 (Snow Leopard) | HDTD_1.0.0.tgz |
Mac OS X 10.9 (Mavericks) | HDTD_1.0.0.tgz |
Browse/checkout source | (username/password: readonly) |
Package Downloads Report | Download Stats |
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