EMDomics
Earth Mover's Distance for Differential Analysis of Genomics Data
Bioconductor version: Release (3.20)
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.
Author: Sadhika Malladi [aut, cre], Daniel Schmolze [aut, cre], Andrew Beck [aut], Sheida Nabavi [aut]
Maintainer: Sadhika Malladi <contact at sadhikamalladi.com> and Daniel Schmolze <emd at schmolze.com>
citation("EMDomics")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("EMDomics")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("EMDomics")
EMDomics Vignette | HTML | R Script |
Reference Manual | ||
NEWS | Text | |
LICENSE | Text |
Details
biocViews | DifferentialExpression, GeneExpression, Microarray, Software |
Version | 2.36.0 |
In Bioconductor since | BioC 3.1 (R-3.2) (9.5 years) |
License | MIT + file LICENSE |
Depends | R (>= 3.2.1) |
Imports | emdist, BiocParallel, matrixStats, ggplot2, CDFt, preprocessCore |
System Requirements | |
URL |
See More
Suggests | knitr |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | EMDomics_2.36.0.tar.gz |
Windows Binary (x86_64) | EMDomics_2.36.0.zip |
macOS Binary (x86_64) | EMDomics_2.36.0.tgz |
macOS Binary (arm64) | EMDomics_2.36.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/EMDomics |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/EMDomics |
Bioc Package Browser | https://code.bioconductor.org/browse/EMDomics/ |
Package Short Url | https://bioconductor.org/packages/EMDomics/ |
Package Downloads Report | Download Stats |