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April 5th, 2025
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NYU Grossman School of Medicine
bioinformatics
biorxiv

FootprintCharter: unsupervised detection and quantification of footprints in single molecule footprinting data

Barzaghi, G.Open in Google Scholar•Krebs, A. R.Open in Google Scholar•Zaugg, J. B.Open in Google Scholar

Single molecule footprinting profiles the heterogeneity of TF occupancy at cis-regulatory elements across cell populations at unprecedented resolution. The single molecule nature of the data in principle allows for observing the footprint of individual transcription factors and nucleosomes. However, we currently lack algorithms to quantify these occupancy patterns of chromatin binding factors in an automated way and without prior assumptions on their genomic location. Here we present FootprintCharter, an unsupervised tool to detect and quantify footprints for transcription factors (TFs) and nucleosomes from single molecule footprinting data. FootprintCharter allows for the quantification of complex molecular states such as positioning of unphased nucleosomes and combinatorial co-binding of multiple TFs.

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