A multi-component power-law penalty corrects distance bias in single-cell co-accessibility and deep-learning chromatin interaction predictions

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Luca Schlegel, Fabio Gómez-Cano, Alexandre P. Marand, Frank M. Johannes
DOI: 10.5281/zenodo.18607659
Cited by: 0

Abstract

This archive contains the source code, penalty parameters, and large-scale penalized co-accessibility datasets for Soybean, Rice, and Maize as described in the associated manuscript.

Fields of Study & Subjects

Genomics and Chromatin Dynamics Chromosomal and Genetic Variations Single-cell and spatial transcriptomics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 February 2026
Language
EN
Document type
Dataset