The EMDomics algorithm is used to perform a supervised multiclass analysis to measure the magnitude and statistical significance of observed continuous genomics data between 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 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 another, 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. This package also incorporates the KomolgorovSmirnov (KS) test and the Cramer von Mises test (CVM), which are both common distribution comparison tests.
Package details 


Author  Sadhika Malladi [aut, cre], Daniel Schmolze [aut, cre], Andrew Beck [aut], Sheida Nabavi [aut] 
Bioconductor views  DifferentialExpression GeneExpression Microarray Software 
Maintainer  Sadhika Malladi <contact@sadhikamalladi.com> and Daniel Schmolze <emd@schmolze.com> 
License  MIT + file LICENSE 
Version  2.6.0 
Package repository  View on Bioconductor 
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