The adaptive immune receptor repertoire community as a model for FAIR stewardship of big immunology data

Jamie K Scott; Felix Breden

doi:10.1016/j.coisb.2020.10.001

The adaptive immune receptor repertoire community as a model for FAIR stewardship of big immunology data

Curr Opin Syst Biol. 2020 Dec:24:71-77. doi: 10.1016/j.coisb.2020.10.001. Epub 2020 Oct 10.

Authors

Jamie K Scott^{1

2}, Felix Breden³

Affiliations

¹ Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
² Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
³ Department of Biological Sciences, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.

Abstract

Systems biology involves network-oriented, computational approaches to modeling biological systems through analysis of big biological data. To contribute maximally to scientific progress, big biological data should be FAIR: findable, accessible, interoperable, and reusable. Here, we describe high-throughput sequencing data that characterize the vast diversity of B- and T-cell clones comprising the adaptive immune receptor repertoire (AIRR-seq data) and its contribution to our understanding of COVID-19 (coronavirus disease 19). We describe the accomplishments of the AIRR community, a grass-roots network of interdisciplinary laboratory scientists, bioinformaticians, and policy wonks, in creating and publishing standards, software and repositories for AIRR-seq data based on the FAIR principles.

Keywords: Adaptive immune receptor repertoire (AIRR) community; Adaptive immunity; B-cell and T-cell receptor repertoires; FAIR Principles; Open source.

Publication types

Review