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RWRtoolkit:在任何物种的多重网络上使用随机游走进行多组学网络分析。

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

作者信息

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

机构信息

Computational and Predictive Biology Group, Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN 37830, USA.

Centre of Excellence for Plant Success in Nature and Agriculture, University of Queensland, St Lucia Campus Mansfield Place St Lucia QLD 4072, Australia.

出版信息

Gigascience. 2025 Jan 6;14. doi: 10.1093/gigascience/giaf028.

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.

摘要

我们介绍了RWRtoolkit,这是一个为R和命令行用户构建的多重生成、探索和统计软件包。RWRtoolkit能够高效探索从自定义实验数据和/或公开可用数据集中生成的大型且高度复杂的生物网络,并且不受物种限制。一系列函数可用于查找生物实体之间的拓扑距离、确定感兴趣集合内的关系、搜索感兴趣集合周围的拓扑背景,以及对集合内和集合间关系的强度进行统计评估。命令行界面专为在高性能集群系统上进行并行化设计,这使得诸如置换检验等高通量分析成为可能。该软件包中的几个工具也已通过KBase网络应用程序在可重复工作流程中可用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c8c/12020474/f17a8cd377cd/giaf028fig1.jpg

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