Evidence map›Paper›PMID 41768797›Full record

ArticleBlood science (Baltimore, Md.)2026

A pipeline for single-cell chromatin accessibility data analysis.

Mengke Zhang, Changya Chen

Abstract read
In one paragraph

Article in Blood science (Baltimore, Md.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mengke ZhangState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China.
Changya ChenState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell chromatin accessibility analysis enables high-resolution dissection of regulatory elements and gene regulatory mechanisms. However, standardized and comprehensive analysis workflows remain limited. In this study, we present a streamlined pipeline for analyzing single-cell chromatin accessibility data. The workflow begins with data preprocessing using single-cell assay for transposase-accessible chromatin (scATAC)-pro or Cell Ranger ATAC, followed by peak calling with MACS2 and differential accessibility analysis to detect open chromatin regions and perform differential accessibility analysis to highlight regulatory differences among cell populations. Transcription factor activity is then inferred using chromVAR, incorporating motif enrichment and footprinting analysis. Finally, SCENIC+ is applied to reconstruct transcriptional regulatory networks, enabling in-depth exploration of epigenetic mechanisms at the single-cell level. This integrative approach offers a robust framework for decoding the regulatory landscape and understanding cellular heterogeneity in complex biological systems.

Indexed as

Single-cell ATAC sequencing

Identifiers

PMID41768797
PMCPMC12944121

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 OpenQuestion graph.