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

Jiang, Jianping; Gu, Jianlei; Zhao, Tingting; Lu, Hui

doi:10.1002/mgg3.641

Cited by 13 publications

(7 citation statements)

References 35 publications

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“…In the field of genomic research, there are several well-known bioinformatics tools that significantly enhance data analysis and visualization capabilities. These include IGV (Integrative Genomics Viewer), which offers an interactive platform for genomic datasets visualization [2]; VCF-Server, tailored for managing and querying Variant Call Format (VCF) files [3]; VCF.Filter, allowing for the intricate filtering of VCF files [4]; and BrowseVCF, providing a user-friendly interface for VCF file exploration [5]. Additionally, GEMINI (Genome Exploration and Mining INteractive Interface) focuses on the 4 integrative analysis and variant prioritization within VCF files [6].…”

Section: Introductionmentioning

confidence: 99%

Variant Graph Craft (VGC): A Comprehensive Tool for Analyzing Genetic Variation and Identifying Disease-Causing Variants

Li,

Yang,

Carneiro

et al. 2023

Preprint

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The Variant Call Format (VCF) file is providing a structured and comprehensive text file that contains essential information about variant positions in the genome, as well as other critical details, such as alleles, genotype calls, and quality scores. Due to its rich data and format, the VCF file has become an increasingly popular resource for researchers and clinicians alike, enabling them to interpret and understand genomic variation data. However, analyzing and visualizing these files poses significant challenges, demanding access to diverse resources and a robust set of features for in-depth exploration. We introduce Variant Graph Craft (VGC), a VCF file visualization and analysis tool offering a wide range of features for exploring genetic variations, including extraction of variant data, intuitive visualization of variants, and the provision of a graphical representation of samples, complete with genotype information. Furthermore, VGC seamlessly integrates with external resources to offer valuable insights into gene function and variant frequencies in sample data. VGC offers gene function and pathway information from Molecular Signatures Database (MSigDB) for GO terms, as well as KEGG, Biocarta, Pathway Interaction Database, and Reactome. Additionally, the tool also provides a dynamic link to gnomAD for variant information, and includes ClinVar data for pathogenic variant information. VGC operates locally, assuring users of data security and privacy by eliminating the need for cloud-based VCF uploads. It supports the Human Genome Assembly Hg37, ensuring compatibility with a wide range of data sets. With its versatility, VGC accommodates various approaches exploring genetic variation data, and can be tailored to the specific needs of the user by using optional phenotype input data. In conclusion, VGC is a useful resource for exploring genetic variation in a secure and user-friendly environment. With its user-tailored set of features, this tool enables researchers and clinicians to easily explore and understand genomic variation data in a comprehensive and accessible manner. From identifying specific genetic mutations to analyzing patterns of variation across the genome, the VCF file visualization and analysis tool is an essential tool for those working in the field of genomics. VGC is freely available athttps://sites.brown.edu/gmilab/variantgraphcraft/

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Section: Introductionmentioning

confidence: 99%

Variant Graph Craft (VGC): A Comprehensive Tool for Analyzing Genetic Variation and Identifying Disease-Causing Variants

Li,

Yang,

Carneiro

et al. 2023

Preprint

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“…The currently available VCF processing programs include SNVerGUI, database.bio, DaMold, mirVAFC, GAVIN, and gNOME [ 35 , 36 , 37 , 38 , 39 , 40 ]. In addition, other tools, such as integrative genomic viewer (IGV), variant call miner (VCF-Miner), VCF.Filter, myVCF, BrowseVCF, and VCF-Server, were also developed to identify disease-associated genetic variants from NGS data [ 41 , 42 , 43 , 44 , 45 , 46 ]. Among these, IGV is the most widely used tool for visualizing genome variation data.…”

Section: Introductionmentioning

confidence: 99%

PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine

Shin

Jeon

Jung

et al. 2022

JPM

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Precision medicine has been revolutionized by the advent of high-throughput next-generation sequencing (NGS) technology and development of various bioinformatic analysis tools for large-scale NGS big data. At the population level, biomedical studies have identified human diseases and phenotype-associated genetic variations using NGS technology, such as whole-genome sequencing, exome sequencing, and gene panel sequencing. Furthermore, patients’ genetic variations related to a specific phenotype can also be identified by analyzing their genomic information. These breakthroughs paved the way for the clinical diagnosis and precise treatment of patients’ diseases. Although many bioinformatics tools have been developed to analyze the genetic variations from the individual patient’s NGS data, it is still challenging to develop user-friendly programs for clinical physicians who do not have bioinformatics programing skills to diagnose a patient’s disease using the genomic data. In response to this demand, we developed a Phenotype to Genotype Variation program (PhenGenVar), which is a user-friendly interface for monitoring the variations in a gene of interest for molecular diagnosis. This allows for flexible filtering and browsing of variants of the disease and phenotype-associated genes. To test this program, we analyzed the whole-genome sequencing data of an anonymous person from the 1000 human genome project data. As a result, we were able to identify several genomic variations, including single-nucleotide polymorphism, insertions, and deletions in specific gene regions. Therefore, PhenGenVar can be used to diagnose a patient’s disease. PhenGenVar is freely accessible and is available at http://dblab.hallym.ac.kr/PhenGenVar.

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“…Whole-genome sequencing (WGS) has been widely used in diagnosing genetic disorders in the pediatrics 1 – 4 , exploring causative relations with tumor progression 5 – 7 , studying genetic variation underlying pharmaceutical response 8 – 10 , performing genome-level comparative analysis 11 , 12 , assessing gene expression 13 – 15 , and providing clinical insights and instructions 16 – 18 . One prominent application with clinical relevance is the utilization of WGS data and bioinformatics tools to identify single nucleotide variants (SNV) and insertion and deletion (INDEL) variants in a single individual genome.…”

Section: Introductionmentioning

confidence: 99%

FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines

et al. 2022

Self Cite

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The quality control of variants from whole-genome sequencing data is vital in clinical diagnosis and human genetics research. However, current filtering methods (Frequency, Hard-Filter, VQSR, GARFIELD, and VEF) were developed to be utilized on particular variant callers and have certain limitations. Especially, the number of eliminated true variants far exceeds the number of removed false variants using these methods. Here, we present an adaptive method for quality control on genetic variants from different analysis pipelines, and validate it on the variants generated from four popular variant callers (GATK HaplotypeCaller, Mutect2, Varscan2, and DeepVariant). FVC consistently exhibited the best performance. It removed far more false variants than the current state-of-the-art filtering methods and recalled ~51-99% true variants filtered out by the other methods. Once trained, FVC can be conveniently integrated into a user-specific variant calling pipeline.

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

Cited by 13 publications

References 35 publications

Variant Graph Craft (VGC): A Comprehensive Tool for Analyzing Genetic Variation and Identifying Disease-Causing Variants

Variant Graph Craft (VGC): A Comprehensive Tool for Analyzing Genetic Variation and Identifying Disease-Causing Variants

PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine

FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines

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