Evidence map›Paper›PMID 42101938›Full record

ArticleSTAR protocols2026

Protocol for identifying cell-type-specific genes associated with disease risk using single-cell eQTL data.

Xin Fang, Lijun Bian, Caiwang Yan, Guangfu Jin

Abstract read
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In one paragraph

Article in STAR protocols, 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

4 authors.

Xin FangDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; State Key Laboratory Cultivation Base of Biomarkers for Cancer Precision Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, China.
Lijun BianDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; State Key Laboratory Cultivation Base of Biomarkers for Cancer Precision Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, China.
Caiwang YanDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Guangfu JinDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; State Key Laboratory Cultivation Base of Biomarkers for Cancer Precision Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, China. Electronic address: guangfujin@njmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Here, we present a protocol for mapping cell-type-specific cis-acting expression quantitative trait loci (cis-eQTLs) in a target tissue and integrating them with genome-wide association study (GWAS) data. We describe pooled-sample multiplexed sequencing, genotype-based cell demultiplexing, cis-eQTL detection in specific cell types, and integration of single-cell eQTLs with GWAS. This protocol facilitates the identification of candidate risk genes and mechanisms underlying disease susceptibility. For complete details on the use and execution of this protocol, please refer to Bian et al.

Indexed as

Genetic Predisposition to DiseaseQuantitative Trait LociSingle-Cell AnalysisGenome-Wide Association StudyHumansPolymorphism, Single NucleotideSingle-Cell Gene Expression AnalysisBioinformaticsGeneticsGenomicsSingle Cell

Identifiers

PMID42101938
PMCPMC13156634

What OpenQuestion holds

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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.