Dataset Information
The discordant method: a novel approach for differential correlation.
Ontology highlight
ABSTRACT: Motivation
Current differential correlation methods are designed to determine molecular feature pairs that have the largest magnitude of difference between correlation coefficients. These methods do not easily capture molecular feature pairs that experience no correlation in one group but correlation in another, which may reflect certain types of biological interactions. We have developed a tool, the Discordant method, which categorizes the correlation types for each group to make this possible.Results
We compare the Discordant method to existing approaches using simulations and two biological datasets with different types of -omics data. In contrast to other methods, Discordant identifies phenotype-related features at a similar or higher rate while maintaining reasonable computational tractability and usability.Availability and implementation
R code and sample data are available at https://github.com/siskac/discordantContact
katerina.kechris@ucdenver.eduSupplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Siska C
PROVIDER: S-EPMC5006287 | biostudies-literature | 2016 Mar
REPOSITORIES: biostudies-literature
Publications
The discordant method: a novel approach for differential correlation.
Bioinformatics (Oxford, England) 20151031 5
<h4>Motivation</h4>Current differential correlation methods are designed to determine molecular feature pairs that have the largest magnitude of difference between correlation coefficients. These methods do not easily capture molecular feature pairs that experience no correlation in one group but correlation in another, which may reflect certain types of biological interactions. We have developed a tool, the Discordant method, which categorizes the correlation types for each group to make this p ...[more]