Navigating the Sequence Read Archive to identify crAssphage, an ubiquitous inhabitant of the human microbiome

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Date
2019-07-14
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Jim Holland Summer Science Research Program Poster Session
Abstract
The declining costs of genome sequencing and growing amounts of genetic data is evolving the field of genomics to become more integrated with computational analysis. The use of high performance clusters(HPC) are necessary to compute the large amounts of data in genomic projects. However, many biologists lack the background experience in working with HPC systems, which limits their ability to best address their research questions. National Center of Genome Analysis Support (NCGAS) is an NSF funded center that focuses on filling this crevice, through helping the research through providing training as workshops, bioinformatics support on projects, and access to compute resources. As a byproduct of helping on research projects, we develop open source workflows and make them available to the community. Here we present a developed workflow that will assist researchers in mining the sequence read archive (SRA), to identify other environments/datasets potentially contain a genome of interest, and identify their closely related genomes. As a proof of concept, we used two genomes to test the developed workflow. We selected these two different genomes to ensure the flexibility of the workflow to generate results in formats to aid further downstream analysis based on the research question.The developed pipeline will be made available through an NSF cloud computing platform, Jetstream with documentation to the research community.
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Sequence Read Archive, Jetstream, bioinformatics, metagenomics
Citation
Jasmine X. Cai, Jania G. Weathers, Haley Leffler, Sruthi Ganapaneni, Bhavya Papudeshi, Sheri A. Sanders and Thomas G. Doak. 2019. Navigating the Sequence Read Archive to identify crAssphage, an ubiquitous inhabitant of the human microbiome. Jim Holland Summer Science Research Program Poster Session, Bloomington, IN. Retrieved from http://hdl.handle.net/2022/23372
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