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

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.

Authors

Publication Details

Journal
Nature Methods
Published
2026-10-08
DOI
https://doi.org/10.1038/s41592-026-03254-z
Primary Topic
Genomics and Chromatin Dynamics
Type
article
Field-Weighted Citation Impact
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article

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

Jacob Matthew Schreiber
Nature Methods
Genomics and Chromatin Dynamics
article

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

Jacob Matthew Schreiber
article en

Abstract

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.

Nature Methods
Openalex Percentile: Top 22%
Genomics and Chromatin Dynamics
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Tangermeme: a toolkit for understanding cis-regulatory logic using deep learning models — Jacob Matthew Schreiber · Nature Methods (2026) | TGRS Research Map | TGRS