Evidence map›Paper›PMID 36685924›Full record

ArticleFrontiers in genetics2022

Forensic efficiencies of individual identification, kinship testing and ancestral inference in three Yunnan groups based on a self-developed multiple DIP panel.

Man Chen, Qiong Lan, Shengjie Nie, Liping Hu, Yating Fang, Wei Cui, Xiaole Bai, Liu Liu, Bofeng Zhu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.4field-weighted citation impact, top 6% of its field
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.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

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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

9 authors at 5 institutions in 1 country.

Man ChenGuangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Qiong LanMicrobiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Shengjie NieSchool of Forensic Medicine, Kunming Medical University, Kunming, China.
Liping HuSchool of Forensic Medicine, Kunming Medical University, Kunming, China.
Yating FangSchool of Basic Medical Sciences, Anhui Medical University, Hefei, China.
Wei CuiGuangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Xiaole BaiGuangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Liu LiuGuangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Bofeng ZhuGuangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
Southern Medical University · CNKunming Medical University · CNAnhui Medical University · CNXi'an Jiaotong University · CNZhujiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deletion/insertion polymorphism (DIP), as a short insertion/deletion sequence polymorphic genetic marker, has attracted the attention of forensic genetic scientist due to its lack of stutter, short amplicon and abundant ancestral information. In this study, based on a self-developed 43 autosomal deletion/insertion polymorphism (A-DIP) loci panel which could meet the forensic application purposes of individual identification, kinship testing and ancestral inference to some extent, we evaluated the forensic efficiencies of the above three forensic objectives in Chinese Yi, Hani and Miao groups of Yunnan province. The cumulative match probability (CPM) and combined probability of exclusion (CPE) of these three groups were 1.11433E-18, 8.24299E-19, 4.21721E-18; 0.999610217, 0.999629285 and 0.999582084, respectively. Average 96.65% full sibling pairs could be identified from unrelated individual pairs (as likelihood ratios > 1) using this DIP panel, whereas the average false positive rate was 3.69% in three target Yunnan groups. With the biogeographical ancestor prediction models constructed by extreme gradient boosting (XGBoost) and support vector machine (SVM) algorithms, 0.8239 (95% CI 0.7984, 0.8474) of the unrelated individuals could be correctly divided according to the continental origins based on the 43 A-DIPs which were large frequency distribution differentiations among different continental populations. The present results of principal component analysis (PCA), multidimensional scaling (MDS), neighbor joining (NJ) and maximum likelihood (ML) phylogenetic trees and STRUCTURE analyses indicated that these three Yunnan groups had relatively close genetic distances with East Asian populations.

Indexed as

deletion/insertion polymorphismextreme gradient boostingfull-sibling identificationindividual identificationsupport vector machine

Identifiers

PMID36685924
PMCPMC9845582
OpenAlexW4313585984

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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.