BioinformaticsBioinformaticsPeer-reviewed journal article
kb_DRAM: Annotating and functional profiling of genomes with DRAM in KBase
Michael ShafferiD, Mikayla BortoniD, Benjamin BolduciD, José P. FariaiD, Rory M. FlynniD, Parsa GhadermaziiD, Janaka N. EdirisingheiD, Elisha M. Wood‐CharlsoniD, Christopher S. MilleriD, Siu Hung Joshua ChaniD, Matthew B. SullivaniD, Christopher S. HenryiD, Kelly C. WrightoniD
Abstract
SummaryAnnotation is predicting the location of and assigning function to genes in a genome. DRAM is a tool developed to annotate bacterial, archaeal and viral genomes derived from pure cultures or metagenomes. DRAM distills multiple gene annotations to summaries of functional potential. Despite these benefits, a downside of DRAM is processing requires large computation resources, which limits its accessibility, and it did not integrate with downstream metabolic modelling tools. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated in the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point and click interface, as well as generate genome scale metabolic models from these DRAM annotations. Availability and ImplementationThe kb_DRAM software is available at https://github.com/shafferm/kb_DRAM. The kb_DRAM apps on KBase can be found in the catalog at https://narrative.kbase.us/#catalog/modules/kb_DRAM. A narrative with examples of running all KBase apps is available at https://kbase.us/n/88325/84/. ContactMichael Shaffer, michael.t.shaffer@colostate.edu; Kelly Wrighton, kelly.wrighton@colostate.edu Supplementary InformationSupplementary data are available at Bioinformatics online.
- organism: bacteria (other)
- organism: virus
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- approach: experimental assay
- Citations
- 18
- FWCI
- 1.60
- Field percentile
- top 17%
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