JCO Clinical Cancer InformaticsBioinformaticsPeer-reviewed journal article
CIViCpy: a Python software development and analysis toolkit for the CIViC knowledgebase
Alex Handler WagneriD, Susanna KiwalaiD, Adam C. CoffmaniD, Joshua F. McMichaeliD, Kelsy C. CottoiD, Thomas B. MooneyiD, Erica Kay BarnelliD, Kilannin KrysiakiD, Arpad M. DanosiD, Jason WalkeriD, Obi L. GriffithiD, Malachi GriffithiD
Abstract
PurposePrecision oncology is dependent upon the matching of tumor variants to relevant knowledge describing the clinical significance of those variants. We recently developed the Clinical Interpretations for Variants in Cancer (CIViC; civicdb.org) crowd-sourced, expert-moderated, open-access knowledgebase, providing a structured framework for evaluating genomic variants of various types (e.g., fusions, SNVs) for their therapeutic, prognostic, predisposing, diagnostic, or functional utility. CIViC has a documented API for accessing CIViC records: Assertions, Evidence, Variants, and Genes. Third-party tools that analyze or access the contents of this knowledgebase programmatically must leverage this API, often reimplementing redundant functionality in the pursuit of common analysis tasks that are beyond the scope of the CIViC web application.\n\nMethodsTo address this limitation, we developed CIViCpy (civicpy.org), a software development kit (SDK) for extracting and analyzing the contents of the CIViC knowledgebase. CIViCpy enables users to query CIViC content as dynamic objects in Python. We assess the viability of CIViCpy as a tool for advancing individualized patient care by using it to systematically match CIViC evidence to observed variants in patient cancer samples.\n\nResultsWe used CIViCpy to evaluate variants from 59,437 sequenced tumors of the AACR Project GENIE dataset. We demonstrate that CIViCpy enables annotation of >1,200 variants per second, resulting in precise variant matches to CIViC level A (professional guideline) or B (clinical trial) evidence for 38.6% of tumors.\n\nConclusionsThe clinical interpretation of genomic variants in cancers requires high-throughput tools for interoperability and analysis of variant interpretation knowledge. These needs are met by CIViCpy, an SDK for downstream applications and rapid analysis. CIViCpy (civicpy.org) is fully documented, open-source, and freely available online.
- Citations
- 12
- FWCI
- 1.61
- Field percentile
- top 18%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- CIViC: A knowledgebase for expert-crowdsourcing the clinical interpretation of variants in cancer.
Malachi Griffith, Nicholas C Spies, … Elaine R Mardis·bioRxiv·Sep 1, 2016
- Evolution of the open-access CIViC knowledgebase is driven by the needsof the cancer variant interpretation community
Kilannin Krysiak, Arpad M. Danos, … Malachi Griffith·bioRxiv·Jun 13, 2021
- The CIViC knowledge model and standard operating procedures for curation and clinical interpretation of variants in cancer
Arpad M. Danos, Kilannin Krysiak, … Obi L. Griffith·Genome MedicinePeer-reviewed·Nov 28, 2019
- CIViC MCP: Integrating Large Language Models with the Clinical Interpretations of Variants in Cancer
Lars E. Schimmelpfennig, Quentin Cody, … Obi L. Griffith·Bioinformatics AdvancesPeer-reviewed·Jan 1, 2026
- Personal Cancer Genome Reporter: Variant Interpretation Report For Precision Oncology
Sigve Nakken, Ghislain Fournous, … Eivind J. Hovig·BioinformaticsPeer-reviewed·Dec 19, 2017
- Identification of community-consensus clinically relevant variants and development of single molecule molecular inversion probes using the CIViC database
Erica Kay Barnell, Adam Waalkes, … Obi L. Griffith·JCO Clinical Cancer InformaticsPeer-reviewed·Oct 16, 2019