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Peer-reviewedCC BYNature Methods

Tangermeme: a toolkit for understanding cis-regulatory logic using deep learning models

  • Jacob Matthew Schreiber1,2
  1. 1Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, USA. [email protected]
  2. 2Research Institute of Molecular Pathology, Vienna BioCenter, Vienna, Austria. [email protected]
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Abstract

Deep learning models have achieved state-of-the-art performance at predicting diverse genomic modalities, yet their promise for biological discovery lies in how they are used after demonstrating their predictive performance. Here we describe the functionality of tangermeme, a highly optimized toolkit for 'everything-but-the-model' when it comes to genomic deep learning, and demonstrate how tangermeme can be used to distill the learned cis-regulatory patterns from models into human-interpretable insights.

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Cite

BibTeXRIS
BibTeX
@article{schreiber2026tangermeme,
  title = {{Tangermeme: a toolkit for understanding cis-regulatory logic using deep learning models}},
  author = {Jacob Matthew Schreiber},
  journal = {Nature Methods},
  year = {2026},
  month = oct,
  doi = {10.1038/s41592-026-03254-z},
  url = {https://doi.org/10.1038/s41592-026-03254-z},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Tangermeme: a toolkit for understanding cis-regulatory logic using deep learning models
AU  - Jacob Matthew Schreiber
PY  - 2026
DA  - 2026/10/08
JO  - Nature Methods
DO  - 10.1038/s41592-026-03254-z
UR  - https://doi.org/10.1038/s41592-026-03254-z
AB  - Deep learning models have achieved state-of-the-art performance at predicting diverse genomic modalities, yet their promise for biological discovery lies in how they are used after demonstrating their predictive performance. Here we describe the functionality of tangermeme, a highly optimized toolkit for 'everything-but-the-model' when it comes to genomic deep learning, and demonstrate how tangermeme can be used to distill the learned cis-regulatory patterns from models into human-interpretable insights.
SN  - 1548-7091
SN  - 1548-7105
ER  -