The EMDomics algorithm is used to perform a supervised twoclass analysis to measure the magnitude and statistical significance of observed continuous genomics data between two groups. Usually the data will be gene expression values from arraybased or sequencebased experiments, but data from other types of experiments can also be analyzed (e.g. copy number variation). Traditional methods like Significance Analysis of Microarrays (SAM) and Linear Models for Microarray Data (LIMMA) use significance tests based on summary statistics (mean and standard deviation) of the two distributions. This approach lacks power to identify expression differences between groups that show high levels of intragroup heterogeneity. The Earth Mover's Distance (EMD) algorithm instead computes the "work" needed to transform one distribution into the other, thus providing a metric of the overall difference in shape between two distributions. Permutation of sample labels is used to generate qvalues for the observed EMD scores.
Package details 


Maintainer  Daniel Schmolze <emd@schmolze.com> 
License  MIT + file LICENSE 
Version  0.99.0 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.