Evidence map›Paper›PMID 40884802›Full record

ArticleGigaScience2025

BVSim: A benchmarking variation simulator mimicking human variation spectrum.

Yongyi Luo, Zhen Zhang, Shu Wang, Jiandong Shi, Jingyu Hao, Sheng Lian, Taobo Hu, Toyotaka Ishibashi, Depeng Wang, Weichuan Yu 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Yongyi LuoDepartment of Statistics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong 999077, China.ORCID 0000-0002-0447-329X
Zhen ZhangDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 999077, China.ORCID 0000-0001-7905-7269
Shu WangDepartment of Breast Surgery, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing 100044, China.ORCID 0000-0002-8651-4795
Jiandong ShiDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 999077, China.ORCID 0000-0002-5178-8470
Jingyu HaoDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 999077, China.ORCID 0000-0002-3301-4439
Sheng LianDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 999077, China.ORCID 0000-0002-0773-8329
Taobo HuDepartment of Breast Surgery, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing 100044, China.ORCID 0000-0001-5124-7167
Toyotaka IshibashiDivision of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 999077, China.ORCID 0000-0001-8015-2319
Depeng WangGrandOmics Biosciences, No.1, East Nengyuan Road, Beijing 102200, China.ORCID 0000-0001-9014-710X
Weichuan YuDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 999077, China.ORCID 0000-0002-5510-6916
Xiaodan FanDepartment of Statistics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong 999077, China.ORCID 0000-0002-2744-9030

Funding

Chinese University of Hong Kong 3136017Hong Kong University of Science and Technology 3030_009Hong Kong University of Science and Technology BGF.001.2023Hong Kong University of Science and Technology Z_1056Innovation and Technology Commission - Hong Kong MHP/033/20Research Grants Council, University Grants Committee C7015-23GResearch Grants Council, University Grants Committee R4012-18Research Grants Council, University Grants Committee T12-101/23-N
6 · The paper itself

Abstract

backgroundGenomic variations, including single-nucleotide polymorphisms, small insertions and deletions, and structural variations, are crucial for understanding evolution and disease. However, comprehensive simulation tools for benchmarking genomic analysis methods are lacking. Existing simulators do not accurately represent the nonuniform distribution and length patterns of structural variations in human genomes, and simulating complex structural variations remains challenging.

resultsWe present BVSim, a flexible tool that provides probabilistic simulations of genomic variations, primarily focusing on human patterns while accommodating diverse species. BVSim effectively simulates both simple and complex structural variations and small variants by mimicking real-life variation distributions, which often exhibit higher frequencies near telomeres and within tandem repeat regions. Notably, BVSim allows users to input single or multiple benchmark samples from any reference genome, enabling the tool to summarize and represent the unique distribution patterns of structural variation positions and lengths specific to those species. Its compatibility with standard file formats facilitates seamless integration into various genomic research workflows, making it a very useful resource for benchmarking downstream tools such as variant callers. With numerical experiments, we show that BVSim generated more realistic sequences significantly different from other simulators' outputs.

conclusionsBVSim is written in Python and freely available to noncommercial users under the GPL3 license. Source code, application guide, and toy examples are provided on the GitHub page at https://github.com/YongyiLuo98/BVSim. The tool is registered in SciCrunch (RRID:SCR_026926), bio.tools (biotools:BVSim), and WorkflowHub (doi:10.48546/WORKFLOWHUB.WORKFLOW.1361.1).

Indexed as

Computational BiologyGenetic VariationGenome, HumanGenomicsSoftwareBenchmarkingComputer SimulationHumansPolymorphism, Single Nucleotidebenchmarkinggenomic variationssequence simulation

Identifiers

PMID40884802
PMCPMC12398280

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.