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Canon, Shane (ORCID:000000028440738X)

Publications and source records attributed to Canon, Shane (ORCID:000000028440738X).

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.

Kainer, David (ORCID:0000000172714676)↗

An integrated metagenomic, metabolomic and transcriptomic survey of Populus across genotypes and environments

Abstract Bridging molecular information to ecosystem-level processes would provide the capacity to understand system vulnerability and, potentially, a means for assessing ecosystem health. Here, we present an integrated dataset containing environmental and metagenomic information from plant-associated microbial communities, plant transcriptomics, plant and soil metabolomics, and soil chemistry and activity characterization measurements derived from the model tree species Populus trichocarpa . Soil, rhizosphere, root endosphere, and leaf samples were collected from 27 different P. trichocarpa genotypes grown in two different environments leading to an integrated dataset of 318 metagenomes, 98 plant transcriptomes, and 314 metabolomic profiles that are supported by diverse soil measurements. This expansive dataset will provide insights into causal linkages that relate genomic features and molecular level events to system-level properties and their environmental influences.

59 BASIC BIOLOGICAL SCIENCES↗