ArticlebioRxiv : the preprint server for biology2023
Assigning credit where it's due: An information content score to capture the clinical value of Multiplexed Assays of Variant Effect.
Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Authors and funding
6 authors.
Funding
Abstract
Background: A variant can be pathogenic or benign with relation to a human disease. Current classification categories from benign to pathogenic reflect a probabilistic summary of current understanding. A primary metric of clinical utility for multiplexed assays of variant effect (MAVE) is the number of variants that can be reclassified from uncertain significance (VUS). However, we hypothesized that this measure of utility underrepresents the information gained from MAVEs and that an information theory approach which includes data that does not reclassify variants will better reflect true information gain. We used this information theory approach to evaluate the information gain, in bits, for MAVEs of Results: Conclusions: An information content approach will more accurately portray information gained through MAVE mapping efforts than counting the number of variants reclassified. This information content approach may also help define the impact of modifying information definitions used to classify many variants, such as guideline rule changes.
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Registered trials
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.