Evidence map›Paper›PMID 41385391›Full record

ReviewBriefings in bioinformatics2025

Assessment and applications of joint profiling of single-cell chromatin accessibility and transcriptome.

Hongfei Li, Jiechen Wang, Qing Liu, Quan Zou, Ximei Luo

Abstract readReview
In one paragraph

Review in Briefings in bioinformatics, 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. Article
  2. 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

5 authors.

Hongfei LiYangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, No. 1 Chengdian Road, Kecheng District, Quzhou 324003, China.ORCID 0000-0003-4104-3966
Jiechen WangYangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, No. 1 Chengdian Road, Kecheng District, Quzhou 324003, China.
Qing LiuDepartment of Anesthesiology, Hospital (T.C.M) Affiliated to Southwest Medical University, No. 319, Section 3, Zhongshan Road, Luzhou 646099, China.
Quan ZouYangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, No. 1 Chengdian Road, Kecheng District, Quzhou 324003, China.ORCID 0000-0001-6406-1142
Ximei LuoYangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, No. 1 Chengdian Road, Kecheng District, Quzhou 324003, China.ORCID 0000-0003-2956-6799

Funding

National Natural Science Foundation of China 62131004National Natural Science Foundation of China 62302342National Natural Science Foundation of China 62371347National Natural Science Foundation of China 62371403
6 · The paper itself

Abstract

Joint profiling technologies combining single-cell chromatin accessibility (CA) and transcriptome sequencing enable cellular heterogeneity analysis from both gene and cis-regulatory element perspectives, greatly advancing molecular biology at a cellular resolution. These techniques have been used to construct gene regulatory networks across diverse cell types and biological tissues, contributing significantly to the mapping of cell developmental trajectories. In this review, we summarize existing single-cell joint profiling methods for CA and transcriptomics and systematically evaluate the data quality of each modality using consistent criteria: the median number of genes detected per cell (RNA) and the median number of accessible peaks per cell (ATAC). Furthermore, we examine relevant bioinformatics tools and highlight their applications in various omics research contexts. Finally, we discuss the current limitations of joint profiling technologies, prospects for future improvement, the extensibility of computational tools, and the potential for co-assaying with additional omics data.

Indexed as

ChromatinGene Expression ProfilingSingle-Cell AnalysisTranscriptomeAnimalsComputational BiologyGene Regulatory NetworksHumansChromatinbioinformatics toolschromatin accessibilitycis-regulatory elementsjoint profilingsingle-cell sequencingtranscriptomics

Identifiers

PMID41385391
PMCPMC12700103

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.