Combining multiplexed functional data to improve variant classification

Jeffrey D Calhoun

doi:10.5281/zenodo.20834698

June 24, 2026Open Access

Combining multiplexed functional data to improve variant classification

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Key Points

This research aims to enhance the classification of genetic variants using multiplexed functional data.
Utilized multiplexed assay for variant effects (MAVEs) to gather functional data.
Strengthened the evidence supporting clinical variant classification.
Focused on reclassifying variants of uncertain significance (VUS).
Increased the accuracy of variant classification.
Reclassified a higher number of VUS based on functional evidence.
Identified potential novel mechanisms of pathogenicity.

Implication

Researchers demonstrate methods to improve variant classification in genes, suggesting new pathogenic mechanisms.

Abstract

By following these steps, researchers can maximize the value of MAVEs, strengthen the functional evidence for clinical variant classification, reclassify more VUS, and potentially uncover novel mechanisms of pathogenicity for clinically relevant genes.

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Cite This Study

Jeffrey D Calhoun (2026) studied this question.

synapsesocial.com/papers/6a3f6772aea7db3c1953edcc https://doi.org/10.5281/zenodo.20834698

View Full Paper

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Combining multiplexed functional data to improve variant classification

Key Points

Implication

Abstract

Discussion

Cite This Study

Combining multiplexed functional data to improve variant classification

Key Points

Implication

Abstract

Discussion

Cite This Study

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