ArticleBMC bioinformatics2025
CoMIT: a bioinformatic pipeline for risk-based prediction of COVID-19 test inclusivity.
Article in BMC bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Crisis-driven innovation in the Republic of Korea's in vitro diagnostics industry: a pandemic case study.Osong public health and research perspectives · 2026Article
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8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe global Coronavirus Disease 2019 (COVID-19) pandemic highlighted the need to quickly diagnose infections to identify and prevent viral spread in the population. In response to the pandemic, BioFire Defense leveraged its PCR-based "lab-in-a-pouch" technology for expedited development of the BioFire® COVID-19 Test, a novel in vitro diagnostic detecting SARS-CoV-2 nucleic acid in human samples. Following clearance of an in vitro diagnostic device, regulatory bodies such as the U.S. Food and Drug Administration (FDA) require regular post market surveillance to monitor test performance against viral lineages circulating in the field, using predictive in silico inclusivity evaluations. Exponential increases in the number of sequences deposited in bioinformatic repositories such as GISAID, during the pandemic, impeded progress in meeting these post market requirements. In response, BioFire Defense developed a new bioinformatic tool to overcome scalability problems and the loss of accuracy encountered with the standard inclusivity method.
resultsThe Coronavirus Monitoring for Inclusivity Tool (CoMIT) uses the Variant Sorter Algorithm to sidestep multiple sequence alignments, a significant barrier inherent in the standard inclusivity method. The implementation of CoMIT and its Variant Sorter Algorithm are described. Automated summary tables and visualizations from a typical inclusivity evaluation are presented. We report our approach to filter and display relevant information in the pipeline outputs using risk factors tied to test performance.
conclusionsBioFire Defense has developed CoMIT, an automated bioinformatic pipeline for efficient processing and reporting of variant inclusivity from the GISAID EpiCoV™ repository. This tool ensures continuous and comprehensive post market evaluations of BioFire COVID-19 Test performance even from datasets large enough to impede standard inclusivity analyses. CoMIT's low computational space complexity and modular code allow this tool to be generalized for inclusivity monitoring of multianalyte or single analyte tests with complex assay designs and/or highly variable targets. CoMIT's databasing capabilities and metadata handling hold the potential for new investigations to improve readiness for future outbreaks.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.