AnFiSA: An open-source computational platform for the analysis of sequencing data for rare genetic disease

M A Bouzinier; D Etin; S I Trifonov; V N Evdokimova; V Ulitin; J Shen; A Kokorev; A A Ghazani; Y Chekaluk; Z Albertyn; A Giersch; C C Morton; F Abraamyan; P K Bendapudi; S Sunyaev; Undiagnosed Diseases Network; Brigham Genomic Medicine; SEQuencing A Baby For An Optimal Outcome; Quantori; J B Krier

doi:10.1016/j.jbi.2022.104174

AnFiSA: An open-source computational platform for the analysis of sequencing data for rare genetic disease

J Biomed Inform. 2022 Sep:133:104174. doi: 10.1016/j.jbi.2022.104174. Epub 2022 Aug 23.

Authors

M A Bouzinier¹, D Etin², S I Trifonov³, V N Evdokimova⁴, V Ulitin³, J Shen⁵, A Kokorev⁶, A A Ghazani⁷, Y Chekaluk⁸, Z Albertyn⁸, A Giersch⁵, C C Morton⁹, F Abraamyan⁸, P K Bendapudi¹⁰, S Sunyaev¹¹, Undiagnosed Diseases Network¹², Brigham Genomic Medicine¹³, SEQuencing A Baby For An Optimal Outcome¹⁴, Quantori¹⁵, J B Krier¹⁶

Affiliations

¹ Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: michael_bouzinier@harvard.edu.
² Forome Association, Boston, MA, USA; Oracle Corporation, USA. Electronic address: dmitry.etin@forome.org.
³ Forome Association, Boston, MA, USA.
⁴ Forome Association, Boston, MA, USA; SBCS Scientific Biomedical Consulting Services, London, UK.
⁵ Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁶ ITMO University, St. Petersburg, Russian Federation.
⁷ Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Brigham Genomic Medicine, Brigham and Women's Hospital, Boston, MA, USA.
⁸ Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁹ Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Manchester Centre for Audiology and Deafness (ManCAD), School of Health Sciences, University of Manchester, UK.
¹⁰ Division of Hemostasis and Thrombosis, Beth Israel Deaconess Medical Center, Boston, MA, USA; Division of Hematology and Blood Transfusion Service, Massachusetts General Hospital, Boston, MA, USA.
¹¹ Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
¹² Undiagnosed Diseases Network, NIH, USA.
¹³ Brigham Genomic Medicine, Brigham and Women's Hospital, Boston, MA, USA.
¹⁴ SEQuencing a Baby for an Optimal Outcome, Brigham and Women's Hospital, Boston, MA, USA.
¹⁵ Quantori, Cambridge, MA, USA.
¹⁶ Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: jkrier@bwh.harvard.edu.

PMID: 35998814
DOI: 10.1016/j.jbi.2022.104174

Abstract

Despite genomic sequencing rapidly transforming from being a bench-side tool to a routine procedure in a hospital, there is a noticeable lack of genomic analysis software that supports both clinical and research workflows as well as crowdsourcing. Furthermore, most existing software packages are not forward-compatible in regards to supporting ever-changing diagnostic rules adopted by the genetics community. Regular updates of genomics databases pose challenges for reproducible and traceable automated genetic diagnostics tools. Lastly, most of the software tools score low on explainability amongst clinicians. We have created a fully open-source variant curation tool, AnFiSA, with the intention to invite and accept contributions from clinicians, researchers, and professional software developers. The design of AnFiSA addresses the aforementioned issues via the following architectural principles: using a multidimensional database management system (DBMS) for genomic data to address reproducibility, curated decision trees adaptable to changing clinical rules, and a crowdsourcing-friendly interface to address difficult-to-diagnose cases. We discuss how we have chosen our technology stack and describe the design and implementation of the software. Finally, we show in detail how selected workflows can be implemented using the current version of AnFiSA by a medical geneticist.

Keywords: Clinical genomics; Diagnostic clinical genomics; Explainable models; Genome annotation; Genome filtering; Genome sequencing; OLAP.

MeSH terms

Computational Biology / methods
Database Management Systems
Databases, Genetic
Genomics* / methods
Reproducibility of Results
Software*
Workflow