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Cloudy with a chance of peptides: accessibility, scalability and reproducibility with cloud-hosted environments

Published

Author(s)

Ben Neely

Abstract

Cloud hosted environments offer known benefits when computational needs outstrip affordable local workstations, enabling high-performance compute without a physical cluster. What has been less apparent, especially to novice users, is the transformative potential for cloud-hosted environments to bridge the digital divide that exists between poorly funded and well-resourced laboratories, and to empower modern research groups with remote personnel and trainees. Using cloud-based proteomic bioinformatic pipelines is not predicated on analyzing thousands of files, but instead can be used to improve accessibility during remote work, extreme weather or working with under-resourced remote trainees. The general benefits of cloud-hosted environments also allow for scalability if needed, but more importantly encourage reproducibility. Since one possible hurdle to adoption is awareness, this paper is written with the non-expert in mind. The benefits and possibilities of using a cloud- hosted environment are emphasized by describing how to setup and analyze a previously published label-free data-dependent acquisition mass spectrometry data set of mammalian urine. Cost and time of analysis are compared using different computational tiers, and important practical considerations are described. Overall, cloud hosted environments offer potential to solve large computational problems, but more importantly can enable and accelerate research in smaller research groups with inadequate infrastructure and suboptimal local computational resources. TOC Graphic
Citation
ACS Journal of Proteome Research
Volume
20
Issue
4

Keywords

cloud computing, remote access, high-performance computing, proteomic workflow

Citation

Neely, B. (2021), Cloudy with a chance of peptides: accessibility, scalability and reproducibility with cloud-hosted environments, ACS Journal of Proteome Research, [online], https://dx.doi.org/10.1021/acs.jproteome.0c00920, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=931422 (Accessed March 29, 2024)
Created January 29, 2021, Updated April 6, 2021