Title | An R package for divergence analysis of omics data. |
Publication Type | Journal Article |
Year of Publication | 2021 |
Authors | Dinalankara W, Ke Q, Geman D, Marchionni L |
Journal | PLoS One |
Volume | 16 |
Issue | 4 |
Pagination | e0249002 |
Date Published | 2021 |
ISSN | 1932-6203 |
Keywords | Databases, Genetic, Genomics, Humans, Neoplasms, Software |
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. |
DOI | 10.1371/journal.pone.0249002 |
Alternate Journal | PLoS One |
PubMed ID | 33819273 |
PubMed Central ID | PMC8021195 |
Grant List | P30 CA006973 / CA / NCI NIH HHS / United States R01 CA200859 / CA / NCI NIH HHS / United States |
Related Lab:
Related Faculty:
Luigi Marchionni, M.D., Ph.D.