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cff-version: 1.2.0
message: 'To cite package "EMDomics" in publications use:'
type: software
license: MIT
title: 'EMDomics: Earth Mover''s Distance for Differential Analysis of Genomics Data'
version: 2.35.0
abstract: The EMDomics algorithm is used to perform a supervised multi-class analysis
  to measure the magnitude and statistical significance of observed continuous genomics
  data between groups. Usually the data will be gene expression values from array-based
  or sequence-based 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 intra-group 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 q-values for
  the observed EMD scores. This package also incorporates the Komolgorov-Smirnov (K-S)
  test and the Cramer von Mises test (CVM), which are both common distribution comparison
  tests.
authors:
- family-names: Malladi
  given-names: Sadhika
  email: contact@sadhikamalladi.com
- family-names: Schmolze
  given-names: Daniel
  email: emd@schmolze.com
- family-names: Beck
  given-names: Andrew
  email: abeck2@bidmc.harvard.edu
- family-names: Nabavi
  given-names: Sheida
  email: sheida_nabavi@hms.harvard.edu
repository: https://bioc.r-universe.dev
contact:
- family-names: Malladi
  given-names: Sadhika
  email: contact@sadhikamalladi.com
- family-names: Schmolze
  given-names: Daniel
  email: emd@schmolze.com