Characterization of intraindividual 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 highdimensional 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.
Package details 


Author  Anestis Touloumis, John C. Marioni and Simon Tavare 
Bioconductor views  DifferentialExpression GeneExpression Genetics Microarray Sequencing Software StatisticalMethod 
Maintainer  Anestis Touloumis <[email protected]> 
License  GPL3 
Version  1.10.0 
Package repository  View on Bioconductor 
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