CIViCpy: A Python Software Development and Analysis Toolkit for the CIViC Knowledgebase

Abstract

PURPOSE Precision oncology depends on 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, and open-access knowledgebase. CIViC provides a structured framework for evaluating genomic variants of various types (eg, fusions, single-nucleotide variants) for their therapeutic, prognostic, predisposing, diagnostic, or functional utility. CIViC has a documented application programming interface 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 application programming interface, 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 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 American Association for Cancer Research Project GENIE data set. 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. CONCLUSION 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, a software development kit for downstream applications and rapid analysis. CIViCpy is fully documented, open-source, and available free online.

Software Development Data Analysis and Processing under the Internet of Things Monitoring System

“…The Internet of Things technology presents the characteristics of integrated development, integrated innovation, large-scale application, and ecological acceleration, and hot technologies continue to emerge [18]. Networks and platforms accelerate large-scale deployment, laying the foundation for the comprehensive promotion of the Internet of Things.…”

Age, Multiple Chronic Conditions, and COVID-19: A Literature Review

“…Ten studies were conducted in China (10,12,16,18,24,(30)(31)(32)34), and 9 of these studies utilized data gathered from patients in Wuhan (10,12,16,18,24,(30)(31)(32)34). Eleven were U.S.-based studies (3 in Washington State (5,15,35), 2 in California (27,28), 1 in Georgia (25), 1 in Michigan (23), 1 in New York (21), and 3 nationwide) (22,26,29). Four studies were based in Italy (6,8,17,33), 1 in Korea (7), and 2 in the United Kingdom (9,11).…”

“…Study sample sizes ranged from 21 (5) to 17,278,392 (11) patients. Five out of 28 studies had less than 100 participants (5,7,10,18,24), 11 studies had between 100 and 1000 participants (8,12,15,16,23,25,(30)(31)(32)34,35), 10 studies had between 1000 and 1,000,000 participants (6,9,10,21,(26)(27)(28)(29)33), and 2 studies had more than 1,000,000 participants (11,22). Participants' age varied widely among the included studies with the mean age ranging from 48 years (22) to 80 years (8).…”

Transformers and the representation of biomedical background knowledge

“…By providing access to a comprehensive knowledge base of genomic annotations, TGex tool simplifies and speeds up the interpretation of variants in clinical genetics processes. Furthermore, Wagner et al [29] provided CIViCpy, an open-source software for extracting and inspection of records from the CIViC database. The delivery of CIViCpy enables the creation of downstream applications and the integration of CIViC into clinical annotation pipelines.…”