Evidence map›Paper›PMID 40049167›Full record

ArticleCell genomics2025

Capturing cell-type-specific activities of cis-regulatory elements from peak-based single-cell ATAC-seq.

Mengjie Chen

Abstract read
In one paragraph

Article in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Crosstalk BetweenCancers · 2026
    Review
  2. Article
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

1 author.

Mengjie ChenDepartment of Medicine, Department of Human Genetics, and Department of Statistics, University of Chicago, Chicago, IL 60637, USA. Electronic address: mengjiechen@uchicago.edu.

Funding

New directions in single cell genomics method developmentR01GM126553 · NIGMS · UNIVERSITY OF CHICAGO · PI Mengjie Chen · 2017 to 2026
$2.9M
Develop new bioinformatics infrastructures and computational tools for epitranscriptomics dataR01HG012927 · NHGRI · UNIVERSITY OF CHICAGO · PI Mengjie Chen · 2023 to 2026
$1.6M
NHGRI NIH HHS R01 HG012927NIGMS NIH HHS R01 GM126553
6 · The paper itself

Abstract

Single-cell ATAC sequencing (scATAC-seq), a state-of-the-art genomic technique designed to map chromatin accessibility at the single-cell level, presents unique analytical challenges due to limited sampling and data sparsity. In this study, we use case studies to highlight the limitations of conventional peak-based methods for processing scATAC-seq data. These methods can fail to capture precise cell-type-specific regulatory signals, producing results that are difficult to interpret and lack portability, thereby compromising the reproducibility of research findings. To overcome these issues, we introduce CREscendo, a method that utilizes Tn5 cleavage frequencies and regulatory annotations to identify differential usage of candidate regulatory elements (CREs) across cell types. Our research advocates for moving away from traditional peak-based quantification in scATAC-seq toward a more robust framework that relies on a standardized reference of annotated CREs, enhancing both the accuracy and reproducibility of genomic studies.

Indexed as

Chromatin Immunoprecipitation SequencingRegulatory Sequences, Nucleic AcidSingle-Cell AnalysisAnimalsChromatinHumansReproducibility of ResultsTransposasesChromatinTn5 transposaseTransposasescis-regulatory elementgene activitiespeak callingscATAC-seqsingle cell

Identifiers

PMID40049167
PMCPMC11960509

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.