Benchmarking interpretability of deep learning for predictive genomics: Recall, precision, and variability of feature attribution

Justin Reynolds; Chongle Pan

doi:10.1371/journal.pcbi.1013784

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Open Access

Peer-reviewed

Research Article

Benchmarking interpretability of deep learning for predictive genomics: Recall, precision, and variability of feature attribution

Justin Reynolds,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization

Affiliation School of Computer Science, Gallogly College of Engineering, University of Oklahoma, Norman, Oklahoma, United States of America

https://orcid.org/0009-0006-7752-3063

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Chongle Pan

Roles Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing

* E-mail: cpan@ou.edu

Affiliation School of Computer Science, Gallogly College of Engineering, University of Oklahoma, Norman, Oklahoma, United States of America

https://orcid.org/0000-0003-2860-0334

⨯

Benchmarking interpretability of deep learning for predictive genomics: Recall, precision, and variability of feature attribution

Justin Reynolds,
Chongle Pan

Published: December 5, 2025
https://doi.org/10.1371/journal.pcbi.1013784

About the Authors

Justin Reynolds

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization

Affiliation School of Computer Science, Gallogly College of Engineering, University of Oklahoma, Norman, Oklahoma, United States of America

https://orcid.org/0009-0006-7752-3063

Chongle Pan

Roles Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing

* E-mail: cpan@ou.edu

Affiliation School of Computer Science, Gallogly College of Engineering, University of Oklahoma, Norman, Oklahoma, United States of America

https://orcid.org/0000-0003-2860-0334

Competing Interests

The authors have declared that no competing interests exist.

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Genome-wide association studies
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Single nucleotide polymorphisms
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Variant genotypes
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Algorithms
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Epistasis
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Memory recall
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Genetics
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Genomics
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