GigaScienceBioinformaticsPeer-reviewed journal article
RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species
David KaineriD, Matthew J. LaneiD, Kyle A. SullivaniD, J Izaak MilleriD, Mikaela CashmaniD, M. MorganiD, Ashley M. CliffiD, Jonathon RomeroiD, Angelica M. WalkeriD, D. Dakota BlairiD, Hari Bahadur ChhetriiD, Yongqin WangiD, Mirko PaviciciD, Anna FurchesiD, Jaclyn M NoshayiD, Meghan M. DrakeiD, Natalie Landry, Amelia IrelandiD, Ali MissaouiiD, Yun Hwan KangiD, John C. SedbrookiD, Paramvir DehaliD, Richard Shane CanoniD, Daniel JacobsoniD
Abstract
Leveraging the use of multiplex multi-omic networks, key insights into genetic and epigenetic mechanisms supporting biofuel production have been uncovered. Here, we introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelisation on high performance cluster systems, which enables high throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.
- Citations
- 11
- FWCI
- 2.69
- Field percentile
- top 9%
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