Ballouz, S., Weber, M., Pavlidis, P., Gillis, J. (February 2017) EGAD: ultra-fast functional analysis of gene networks. Bioinformatics, 33 (4). pp. 612-614. ISSN 1367-4803
Abstract
Evaluating gene networks with respect to known biology is a common task but often a computationally costly one. Many computational experiments are difficult to apply exhaustively in network analysis due to run-times. To permit high-throughput analysis of gene networks, we have implemented a set of very efficient tools to calculate functional properties in networks based on guilt-by-association methods. EGAD: ( E: xtending ' G: uilt-by- A: ssociation' by D: egree) allows gene networks to be evaluated with respect to hundreds or thousands of gene sets. The methods predict novel members of gene groups, assess how well a gene network groups known sets of genes, and determines the degree to which generic predictions drive performance. By allowing fast evaluations, whether of random sets or real functional ones, EGAD: provides the user with an assessment of performance which can easily be used in controlled evaluations across many parameters. AVAILABILITY AND IMPLEMENTATION: The software package is freely available at https://github.com/sarbal/EGAD and implemented for use in R and Matlab. The package is also freely available under the LGPL license from the Bioconductor web site (http://bioconductor.org). CONTACT: JGillis@cshl.eduSupplementary information: Supplementary data are available at Bioinformatics online.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene network |
| CSHL Authors: | |
| Communities: | CSHL labs > Gillis Lab |
| Depositing User: | Matt Covey |
| Date: | February 2017 |
| Date Deposited: | 16 Feb 2017 20:44 |
| Last Modified: | 06 Jul 2021 18:32 |
| PMCID: | PMC6041978 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/34122 |
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