An R Package for Divergence Analysis of Omics Data
Wikum DinalankaraiD, Qian KeiD, Donald Geman, Luigi MarchionniiD
Abstract
Given the ever-increasing amount of high-dimensional and complex omics data becoming available, it is increasingly important to discover simple but effective methods of analysis. Divergence analysis transforms each entry of a high-dimensional omics profile into a digitized (binary or ternary) code based on the deviation of the entry from a given baseline population. This is a novel framework that is significantly different from existing omics data analysis methods: it allows digitization of continuous omics data at the univariate or multivariate level, facilitates sample level analysis, and is applicable on many different omics platforms. The divergence package, available on the R platform through the Bioconductor repository collection, provides easy-to-use functions for carrying out this transformation. Here we demonstrate how to use the package with data from the Cancer Genome Atlas.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 2
- FWCI
- 0.16
- Field percentile
- 37th percentile
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Software For The Integration Of Multi-Omics Experiments In Bioconductor
Marcel Ramos, Lucas Schiffer, … Levi Waldron·Cancer ResearchPeer-reviewed·Oct 31, 2017
- OmicsOne: Associate Omics Data with Phenotypes in One-Click
Yingwei Hu, Minghui Ao, Hui Zhang·bioRxiv·Sep 5, 2019
- eOmics: an R package for improved omics data analysis
Yu Liu·bioRxiv·Mar 11, 2023
- mixOmics: an R package for ‘omics feature selection and multiple data integration
Florian Rohart, Benoît Gautier, … Kim‐Anh Lê Cao·PLoS Computational BiologyPeer-reviewed·Nov 3, 2017
- RadarOmics: Intuitive visualisation of multidimensional omics data in ecological, evolutionary, and developmental studies
Emma Gairin, Vincent Laudet, Marcela Herrera·bioRxiv·Jan 15, 2026
- MOVIE: Multi-Omics VIsualization of Estimated contributions
Sean McCabe, Danyu Y. Lin, Michael I. Love·bioRxiv·Jul 29, 2018