CIViCpy: a Python software development and analysis toolkit for the CIViC knowledgebase

Purpose: Precision 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. Methods: To 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. Results: We 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. Conclusions: The 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.