RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

David Kainer; Matthew Lane; Kyle A. Sullivan; J. Izaak Miller; Mikaela Cashman; Mallory Morgan; Ashley Cliff; Jonathon Romero; Angelica Walker; D. Dakota Blair; Hari Chhetri; Yongqin Wang; Mirko Pavicic; Anna Furches; Jaclyn Noshay; Meghan Drake; A. J. Ireland; Ali Missaoui; Yun Kang; John C. Sedbrook; Paramvir Dehal; Shane Canon; Daniel Jacobson

doi:10.1093/gigascience/giaf028

RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

David Kainer, Matthew Lane, Kyle A. Sullivan, J. Izaak Miller, Mikaela Cashman, Mallory Morgan, Ashley Cliff, Jonathon Romero, Angelica Walker, D. Dakota Blair, Hari Chhetri, Yongqin Wang, Mirko Pavicic, Anna Furches, Jaclyn Noshay, Meghan Drake, A. J. Ireland, Ali Missaoui, Yun Kang, John C. SedbrookParamvir Dehal, Shane Canon, Daniel Jacobson

Research output: Contribution to journal › Article › peer-review

Abstract

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 parallelization 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.

Original language	English
Article number	giaf028
Journal	GigaScience
Volume	14
DOIs	https://doi.org/10.1093/gigascience/giaf028
State	Published - 2025

Funding

This manuscript has been authored by UT-Battelle, LLC under contract number DE-AC05-00OR22725 with the US Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the US Department of Energy under contract number DE-AC05-00OR22725. The switchgrass resequencing data were produced by the US Department of Energy Joint Genome Institute (https://ror.org/04xm1d337; operated under contract number DEAC02-05CH11231) in collaboration with the user community. Sujan Mamidi performed sequence alignments and called the SNP variants, and Jeremy Schmutz leads the HudsonAlpha sequencing efforts. This work is supported as part of the Genomic Sciences Program DOE Systems Biology Knowledgebase (KBase) funded by the Office of Biological and Environmental Research\u2019s Genomic Science program within the US Department of Energy Office of Science under award number DE-AC02-05CH11231. This work was also funded by The Center for Bioenergy Innovation (CBI), which is a US Department of Energy Bioenergy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science. Support was also provided by the Integrated Pennycress Resilience Project (IPReP), funded by the Office of Biological and Environmental Research\u2019s Genomic Science program within the US Department of Energy Office of Science. This research is additionally supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Genomic Science Program grant number DE-SC0021286. Oak Ridge National Laboratory is managed by UT-Battelle, LLC for the US DOE under contract number DE-AC05-00OR22725.

Keywords

multi-omic
multiplex network
random walk with restart
software package
systems biology

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10.1093/gigascience/giaf028

Cite this

Kainer, D., Lane, M., Sullivan, K. A., Miller, J. I., Cashman, M., Morgan, M., Cliff, A., Romero, J., Walker, A., Dakota Blair, D., Chhetri, H., Wang, Y., Pavicic, M., Furches, A., Noshay, J., Drake, M., Ireland, A. J., Missaoui, A., Kang, Y., ... Jacobson, D. (2025). RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species. GigaScience, 14, Article giaf028. https://doi.org/10.1093/gigascience/giaf028

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title = "RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species",

abstract = "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 parallelization 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.",

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author = "David Kainer and Matthew Lane and Sullivan, \{Kyle A.\} and Miller, \{J. Izaak\} and Mikaela Cashman and Mallory Morgan and Ashley Cliff and Jonathon Romero and Angelica Walker and D. Dakota Blair and Hari Chhetri and Yongqin Wang and Mirko Pavicic and Anna Furches and Jaclyn Noshay and Meghan Drake and Ireland, \{A. J.\} and Ali Missaoui and Yun Kang and Sedbrook, \{John C.\} and Paramvir Dehal and Shane Canon and Daniel Jacobson",

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doi = "10.1093/gigascience/giaf028",

language = "English",

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Kainer, D, Lane, M, Sullivan, KA, Miller, JI, Cashman, M, Morgan, M, Cliff, A, Romero, J, Walker, A, Dakota Blair, D, Chhetri, H, Wang, Y, Pavicic, M, Furches, A, Noshay, J, Drake, M, Ireland, AJ, Missaoui, A, Kang, Y, Sedbrook, JC, Dehal, P, Canon, S & Jacobson, D 2025, 'RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species', GigaScience, vol. 14, giaf028. https://doi.org/10.1093/gigascience/giaf028

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AU - Kainer, David

AU - Lane, Matthew

AU - Sullivan, Kyle A.

AU - Miller, J. Izaak

AU - Cashman, Mikaela

AU - Morgan, Mallory

AU - Cliff, Ashley

AU - Romero, Jonathon

AU - Walker, Angelica

AU - Dakota Blair, D.

AU - Chhetri, Hari

AU - Wang, Yongqin

AU - Pavicic, Mirko

AU - Furches, Anna

AU - Noshay, Jaclyn

AU - Drake, Meghan

AU - Ireland, A. J.

AU - Missaoui, Ali

AU - Kang, Yun

AU - Sedbrook, John C.

AU - Dehal, Paramvir

AU - Canon, Shane

AU - Jacobson, Daniel

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RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

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