Scalable in-memory processing of omics workflows.
| Autor: | Elisseev V; IBM Research Europe, Hartree Centre, Daresbury Laboratory, Keckwick Lane, WarringtonWA4 4AD, Cheshire, UK.; Wrexham Glyndwr University, Mold Rd, Wrexham LL11 2AW, Wales, UK., Gardiner LJ; IBM Research Europe, Hartree Centre, Daresbury Laboratory, Keckwick Lane, WarringtonWA4 4AD, Cheshire, UK., Krishna R; IBM Research Europe, Hartree Centre, Daresbury Laboratory, Keckwick Lane, WarringtonWA4 4AD, Cheshire, UK. |
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| Jazyk: | angličtina |
| Zdroj: | Computational and structural biotechnology journal [Comput Struct Biotechnol J] 2022 Apr 20; Vol. 20, pp. 1914-1924. Date of Electronic Publication: 2022 Apr 20 (Print Publication: 2022). |
| DOI: | 10.1016/j.csbj.2022.04.014 |
| Abstrakt: | We present a proof of concept implementation of the in-memory computing paradigm that we use to facilitate the analysis of metagenomic sequencing reads. In doing so we compare the performance of POSIX™file systems and key-value storage for omics data, and we show the potential for integrating high-performance computing (HPC) and cloud native technologies. We show that in-memory key-value storage offers possibilities for improved handling of omics data through more flexible and faster data processing. We envision fully containerized workflows and their deployment in portable micro-pipelines with multiple instances working concurrently with the same distributed in-memory storage. To highlight the potential usage of this technology for event driven and real-time data processing, we use a biological case study focused on the growing threat of antimicrobial resistance (AMR). We develop a workflow encompassing bioinformatics and explainable machine learning (ML) to predict life expectancy of a population based on the microbiome of its sewage while providing a description of AMR contribution to the prediction. We propose that in future, performing such analyses in 'real-time' would allow us to assess the potential risk to the population based on changes in the AMR profile of the community. Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (© 2022 The Author(s).) |
| Databáze: | MEDLINE |
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