Ten simple rules for large-scale data processing

Arkarachai Fungtammasan; Alexandra Lee; Jaclyn Taroni; Kurt Wheeler; Chen-Shan Chin; Sean Davis; Casey Greene

doi:10.1371/journal.pcbi.1009757

Ten simple rules for large-scale data processing

PLoS Comput Biol. 2022 Feb 10;18(2):e1009757. doi: 10.1371/journal.pcbi.1009757. eCollection 2022 Feb.

Authors

Arkarachai Fungtammasan¹, Alexandra Lee², Jaclyn Taroni³, Kurt Wheeler³, Chen-Shan Chin¹, Sean Davis^{4

5}, Casey Greene^{4

6}

Affiliations

¹ DNAnexus, Inc., Mountain View, California, United States of America.
² Genomics and Computational Biology Graduate Program, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
³ Childhood Cancer Data Lab, Alex's Lemonade Stand Foundation, Philadelphia, Pennsylvania, United States of America.
⁴ Center for Health AI, University of Colorado Anschutz School of Medicine, Aurora, Colorado, United States of America.
⁵ Department of Medicine, Divisions of Medical Oncology and Hematology, University of Colorado Anschutz School of Medicine, Aurora, Colorado, United States of America.
⁶ Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz School of Medicine, Aurora, Colorado, United States of America.

No abstract available

Publication types

Editorial
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Guidelines as Topic*

Grants and funding

This work was supported in part by Alex’s Lemonade Stand Foundation, Childhood Cancer Data Lab (JT and KW) as well as grants from the Gordon and Betty Moore Foundation (GBMF 4552) and the National Institutes of Health’s National Human Genome Research Institute (R01 HG010067). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.