Evidence map›Paper›PMID 31127704›Full record

ArticleMolecular genetics & genomic medicine2019

VCF-Server: A web-based visualization tool for high-throughput variant data mining and management.

Jianping Jiang, Jianlei Gu, Tingting Zhao, Hui Lu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular genetics & genomic medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  8. GAMUT: A genomics big data management tool.Journal of biosciences · 2021
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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

4 authors.

Jianping JiangDepartment of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, College of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0002-1066-6362
Jianlei GuDepartment of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, College of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Tingting ZhaoDepartment of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, College of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Hui LuDepartment of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, College of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0001-8347-0830

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNext-generation sequencing (NGS) has been widely used in both clinics and research. It has become the most powerful tool for diagnosing genetic disorders and investigating disease etiology through the discovery of genetic variants. Variants identified by NGS are stored in variant call format (VCF) files. However, querying and filtering VCF files are extremely difficult for researchers without programming skills. Furthermore, as the mutation data are increasing exponentially, there is an urgent need to develop tools to manage these variant data in a centralized way.

methodsThe VCF-Server was developed as a web-based visualization tool to support the interactive analysis of genetic variant data. It allows researchers and medical geneticists to manage, annotate, filter, query, and export variants in a fast and effective way.

resultsIn this study, we developed the VCF-Server, a powerful and easily accessible tool for researchers and medical geneticists to perform variant analysis. Users can query VCFs, annotate, and filter variants without knowing programming code. Once the VCF file is uploaded, VCF-Server allows users to annotate the VCF with commonly used databases or user-defined variant annotations (including variant blacklist and whitelist). Variant information in the VCF is shown visually via the interactive graphical interface. Users can filter the variants with flexible filtering rules, and the prioritized variants can be exported locally for further analysis. As VCF-Server adopts a web file system, files in the VCF-Server can be stored and managed in a centralized way. Moreover, VCF-Server allows direct web-based analysis (accessible through either desktop computers or mobile devices) as well as local deployment.

conclusionsWith an easy-to-use graphical interface, VCF-Server allows researchers with little bioinformatics background to explore and mine mutation data, which may broaden the application of NGS technology in clinics and research. The tool is freely available for use at https://www.diseasegps.org/VCF-Server?lan = eng.

Indexed as

Data MiningUser-Computer InterfaceDatabases, GeneticGenetic VariationHigh-Throughput Nucleotide SequencingHumansInternetSequence Analysis, DNANGSsoftwarevariant filteringvariant managementVCF visualization

Identifiers

PMID31127704
PMCPMC6625089

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LicenceCC BY
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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.