Evidence map›Paper›PMID 40184433›Full record

ArticleGigaScience2025

VCF2Dis: an ultra-fast and efficient tool to calculate pairwise genetic distance and construct population phylogeny from VCF files.

Lian Xu, Weiming He, Shuaishuai Tai, Xiaoli Huang, Mumu Qin, Xun Liao, Yi Jing, Jian Yang, Xiaodong Fang, Jianhua Shi and 1 more

Abstract read
In one paragraph

Article in GigaScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

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0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

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  13. Analysis of Genetic Diversity in Speckled Blue Grouper (Animals : an open access journal from MDPI · 2026
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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

11 authors.

Lian XuInstitute for Translational Neuroscience of Affiliated Hospital 2 of Nantong University, Center for Neural Developmental and Degenerative Research of Nantong University, Key Laboratory of Neurodegenerative Diseases, Nantong, Jiangsu 226014, China.ORCID 0000-0003-1685-605X
Weiming HeBGI Research, Shenzhen 518083, China.ORCID 0000-0003-0483-5390
Shuaishuai TaiBGI Research, Shenzhen 518083, China.ORCID 0000-0001-8204-6982
Xiaoli HuangInstitute for Translational Neuroscience of Affiliated Hospital 2 of Nantong University, Center for Neural Developmental and Degenerative Research of Nantong University, Key Laboratory of Neurodegenerative Diseases, Nantong, Jiangsu 226014, China.ORCID 0009-0003-7923-4386
Mumu QinBGI Research, Sanya 572025, China.ORCID 0009-0008-9940-6225
Xun LiaoBGI Research, Shenzhen 518083, China.ORCID 0000-0002-6789-4358
Yi JingBGI Research, Sanya 572025, China.ORCID 0000-0002-5424-9106
Jian YangKey Laboratory of Neuroregeneration, Ministry of Education and Jiangsu Province, Co-innovation Center of Neuroregeneration, NMPA Key Laboratory for Research and Evaluation of Tissue Engineering Technology Products, Nantong University, Nantong, Jiangsu 226001, China.ORCID 0000-0001-6318-8854
Xiaodong FangBGI Research, Shenzhen 518083, China.ORCID 0000-0001-7061-3337
Jianhua ShiInstitute for Translational Neuroscience of Affiliated Hospital 2 of Nantong University, Center for Neural Developmental and Degenerative Research of Nantong University, Key Laboratory of Neurodegenerative Diseases, Nantong, Jiangsu 226014, China.ORCID 0000-0002-5351-406X
Nana JinInstitute for Translational Neuroscience of Affiliated Hospital 2 of Nantong University, Center for Neural Developmental and Degenerative Research of Nantong University, Key Laboratory of Neurodegenerative Diseases, Nantong, Jiangsu 226014, China.ORCID 0009-0006-5522-3991

Funding

Hainan Seed Industry Laboratory JBGS-B23YQ2001National Natural Science Foundation of China 82171425Project of Sanya Yazhou Bay Science and Technology City SKJC-2023-02-002Second Affiliated Hospital of Nantong University YJRCJJ001Shuangchuang Doctor Program of Jiangsu Province JSSCBS20211127
6 · The paper itself

Abstract

backgroundGenetic distance metrics are crucial for understanding the evolutionary relationships and population structure of organisms. Progress in next-generation sequencing technology has given rise of genotyping data of thousands of individuals. The standard Variant Call Format (VCF) is widely used to store genomic variation information, but calculating genetic distance and constructing population phylogeny directly from large VCF files can be challenging. Moreover, the existing tools that implement such functions remain limited and have low performance in processing large-scale genotype data, especially in the area of memory efficiency.

findingsTo address these challenges, we introduce VCF2Dis, an ultra-fast and efficient tool that calculates pairwise genetic distance directly from large VCF files and then constructs distance-based population phylogeny using the ape package. Benchmarking results demonstrate the tool's efficiency, with rapid processing times, minimal memory usage (e.g., 0.37 GB for the complete analysis of 2,504 samples with 81.2 million variants), and high accuracy, even when handling datasets with millions of variants from thousands of individuals. Its straightforward command-line interface, compatibility with downstream phylogenetic analysis tools (e.g., MEGA, Phylip, and FastTree), and support for multithreading make it a valuable tool for researchers studying population relationships. These advantages meaning VCF2Dis has already been widely utilized in many published genomic studies.

conclusionWe present VCF2Dis, a straightforward and efficient tool for calculating genetic distance and constructing population phylogeny directly from large-scale genotype data. VCF2Dis has been widely applied, facilitating the exploration of population relationship in extensive genome sequencing studies.

Indexed as

Computational BiologyGenetics, PopulationPhylogenySoftwareGenetic VariationGenomicsHigh-Throughput Nucleotide SequencingHumansp-distancepopulation phylogenyVCFVCF2Dis

Identifiers

PMID40184433
PMCPMC11970368

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LicenceCC BY
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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.