FiberBrowser: a unified framework for single-molecule genomics

FiberBrowser with FiberHMM converts four single-molecule footprinting assays into a shared per-molecule map of nucleosomes, accessible DNA, and subnucleosomal footprints, enabling cross-assay modeling.

• Why it matters: Single-fiber footprinting reveals heterogeneity that bulk methods average out, but differing enzyme chemistries and sequencing platforms make results hard to compare or reuse.
• What they did: FiberHMM scores each observation using assay-specific informative sites and sequence-specific modification probabilities, distinguishing missing data from protection across four assays.
• The result: A classifier trained on Fiber-seq footprints correctly identifies 12 scDAF-seq cells as lymphoblastoid without retraining, and the chemistry-independent representation supports model transfer where raw patterns do not.

AI summary of the abstract · may contain errors · not medical advice · read the paper.