Evidence map›Paper›PMID 42894038›Full record

ReviewInternational journal of legal medicine2026

Single-cell strategies for the interpretation of complex forensic DNA mixtures: isolation techniques, genotype data integration, and prospects for application.

Ruijia Liu, Zheng Wang, Jing Liu

Abstract readReview
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In one paragraph

Review in International journal of legal medicine, 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

3 authors.

Ruijia LiuInstitute of Forensic Medicine, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, 610041, Chengdu, China.
Zheng WangInstitute of Forensic Medicine, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, 610041, Chengdu, China. wangzhengtim@scu.edu.cn.ORCID http://orcid.org/0000-0003-3419-1741
Jing LiuInstitute of Forensic Medicine, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, 610041, Chengdu, China. liujing2381@scu.edu.cn.ORCID http://orcid.org/0009-0007-1356-0073

Funding

National Natural Science Foundation of China 82502274Sichuan Postdoctoral Research Project Special Funding TB2025017
6 · The paper itself

Abstract

Complex forensic DNA mixtures remain challenging to interpret, especially when contributor proportions are highly imbalanced or when the mixture involves the same cell type. Single-cell isolation strategies have provided a novel methodological approach for overcoming these technical limitations. This review provides a summary of recent advances in single-cell isolation techniques for complex forensic DNA mixtures. It covers three major categories of techniques: micromanipulation and laser capture microdissection (LCM); fluorescence‑activated cell sorting (FACS) paired with imaging flow cytometry (IFC); and microfluidic‑based systems represented by the DEPArray™ platform. The performance of these techniques is comparatively evaluated in terms of throughput, sample adaptability, and cost. We further discuss key challenges in single‑cell STR profiling, such as allelic drop‑out (ADO) and allelic drop‑in (ADI), and summarize strategies for multi‑single‑cell clustering, consensus genotype reconstruction, and probabilistic evidence interpretation. Finally, the forensic value of single-cell strategies is emphasized. The future directions include the integration of automation and high‑throughput workflows, artificial intelligence-assisted analysis, as well as the development of standardized interpretation frameworks.

Indexed as

Complex DNA mixturesData integrationForensic applicationsSingle-cell isolationSTR genotyping

Identifiers

What OpenQuestion holds

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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 OpenQuestion graph.