Evidence map›Paper›PMID 40424338›Full record

ArticleBioinformatics (Oxford, England)2025

scNucMap: mapping the nucleosome landscapes at single-cell resolution.

Qianming Xiang, Binbin Lai

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Qianming XiangInstitute of Medical Technology, Peking University Health Science Center, Beijing 100191, China.ORCID 0000-0002-0372-2792
Binbin LaiInstitute of Medical Technology, Peking University Health Science Center, Beijing 100191, China.ORCID 0000-0002-2831-2677

Funding

National Natural Science Foundation of China 32070686
6 · The paper itself

Abstract

motivationNucleosome depletion around cis-regulatory elements (CREs) is associated with CRE activity and implies the underlying gene regulatory network. Single-cell micrococcal nuclease sequencing (scMNase-seq) enables the simultaneous measurement of nucleosome positioning and chromatin accessibility at single-cell resolution, thereby capturing cellular heterogeneity in epigenetic regulation. However, there is currently no computational tool specifically designed to decode scMNase-seq data, impeding the generation of more precise and context-dependent insights into chromatin dynamics and gene regulation.

resultsHere, we present scNucMap, a tool designed to leverage the unique characteristics of scMNase-seq data to map the landscapes of candidate nucleosome-free regions (NFRs). scNucMap demonstrated superior performance and robustness in cell clustering on scMNase-seq data compared to Signac and chromVAR across diverse sample compositions and data complexities, achieving higher overall accuracy and Kappa coefficients. Additionally, scNucMap identified significant TFs associated with nucleosome depletion at CREs at both single-cell and cell-cluster levels, thereby facilitating cell-type annotation and regulatory network inference. When applied to scATAC-seq data, scNucMap enriched standard analyses with complementary insights into nucleosome architecture, underscoring its cross‑modality versatility. Overall, scNucMap exhibits both high reliability and adaptability, making it an effective tool for analyzing scMNase-seq data and supporting multimodal studies, thereby illuminating the intricate relationship between regulatory networks and nucleosome positioning at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: scNucMap is available at https://github.com/qianming-bioinfo/scNucMap.

Indexed as

NucleosomesSingle-Cell AnalysisSoftwareGene Regulatory NetworksHumansMicrococcal NucleaseRegulatory Sequences, Nucleic AcidSequence Analysis, DNAMicrococcal NucleaseNucleosomes

Identifiers

PMID40424338
PMCPMC12202765

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.