FiberBrowser: a unified framework for single-molecule genomics
Abstract
Single-molecule footprinting methods are rapidly transforming chromatin biology. They resolve nucleosome positioning, regulatory-factor occupancy, and accessibility on individual DNA fibers, revealing combinatorial heterogeneity that bulk measurements average away. Emerging footprinting methods leverage diverse enzyme systems and sequencing platforms, necessitating tools that can accommodate these systems. We present FiberBrowser, a unified platform that converts these diverse datasets into a common per-molecule representation of nucleosomes, accessible DNA, and subnucleosomal footprints for interactive and scripted analyses. Its inference engine, FiberHMM, weighs each observation against the assay's informative sites and sequence-specific modification probabilities, separating missing information from protection in four assays. FiberBrowser clusters, sorts and compares these calls across thousands of molecules in seconds, linking chromatin architecture to haplotype, CpG methylation and non-reference structural variants on the same molecules. Because the representation is independent of chemistry, models also transfer between assays. A classifier trained on Fiber-seq footprints identifies 12 scDAF-seq cells as lymphoblastoid without retraining, whereas models trained on raw modification patterns fail to transfer. FiberBrowser thus provides a unified, expandable analytical framework for single-molecule chromatin footprinting.
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BibTeX
@misc{tullius2026fiberbrowser,
title = {{FiberBrowser: a unified framework for single-molecule genomics}},
author = {Thomas W. Tullius and Christopher Catalano and Jane Ranchalis and Jie Hu and Mitchell R. Vollger and Andrew B. Stergachis and Michael S. Levine},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.29.762797},
url = {https://www.biorxiv.org/content/10.64898/2026.10.29.762797v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - FiberBrowser: a unified framework for single-molecule genomics
AU - Thomas W. Tullius
AU - Christopher Catalano
AU - Jane Ranchalis
AU - Jie Hu
AU - Mitchell R. Vollger
AU - Andrew B. Stergachis
AU - Michael S. Levine
PY - 2026
DA - 2026/10/29
PB - bioRxiv
DO - 10.64898/2026.10.29.762797
UR - https://www.biorxiv.org/content/10.64898/2026.10.29.762797v1
AB - Single-molecule footprinting methods are rapidly transforming chromatin biology. They resolve nucleosome positioning, regulatory-factor occupancy, and accessibility on individual DNA fibers, revealing combinatorial heterogeneity that bulk measurements average away. Emerging footprinting methods leverage diverse enzyme systems and sequencing platforms, necessitating tools that can accommodate these systems. We present FiberBrowser, a unified platform that converts these diverse datasets into a common per-molecule representation of nucleosomes, accessible DNA, and subnucleosomal footprints for interactive and scripted analyses. Its inference engine, FiberHMM, weighs each observation against the assay's informative sites and sequence-specific modification probabilities, separating missing information from protection in four assays. FiberBrowser clusters, sorts and compares these calls across thousands of molecules in seconds, linking chromatin architecture to haplotype, CpG methylation and non-reference structural variants on the same molecules. Because the representation is independent of chemistry, models also transfer between assays. A classifier trained on Fiber-seq footprints identifies 12 scDAF-seq cells as lymphoblastoid without retraining, whereas models trained on raw modification patterns fail to transfer. FiberBrowser thus provides a unified, expandable analytical framework for single-molecule chromatin footprinting.
SN - 2692-8205
ER -