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August 16, 2025Open Access

Comparative evaluation of genomic footprinting algorithms for predicting transcription factor binding sites in single-cell data

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Authors

AEAmanda EverittSWSean WhalenKPKatherine S. Pollard

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Overview

Benchmarking reveals transcription factor binding site predictions in single-cell data, indicating method consistency and improvements.

Key Points

  • Binding sites are influenced by genomic footprinting, which identifies specific sites in single-cell contexts.
  • The study identified peak-level read coverage as a key predictor of stable footprints for transcription factors.
  • A benchmarking framework was developed to assess methods for transcript factor binding in single-cell data models.
  • Practical guidelines aim to enhance genomic footprinting and understanding gene regulatory networks in tissues.

Cite This Study

Everitt et al. (2025) studied this question.

synapsesocial.com/papers/68c23626b210217d647738fahttps://doi.org/10.1101/2025.08.07.669008
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