Department of Computer Science, Brown University, Providence, RI, 02912, USA.
Department of Chemistry, Brown University, Providence, RI, 02912, USA.
BMC Bioinformatics. 2024 Sep 3;25(1):288. doi: 10.1186/s12859-024-05875-7.
The variant call format (VCF) file is a structured and comprehensive text file crucial for researchers and clinicians in interpreting and understanding genomic variation data. It contains essential information about variant positions in the genome, along with alleles, genotype calls, and quality scores. Analyzing and visualizing these files, however, poses significant challenges due to the need for diverse resources and robust features for in-depth exploration.
To address these challenges, we introduce variant graph craft (VGC), a VCF file visualization and analysis tool. VGC offers a wide range of features for exploring genetic variations, including extraction of variant data, intuitive visualization, and graphical representation of samples with genotype information. VGC is designed primarily for the analysis of patient cohorts, but it can also be adapted for use with individual probands or families. It integrates seamlessly with external resources, providing insights into gene function and variant frequencies in sample data. VGC includes gene function and pathway information from Molecular Signatures Database (MSigDB) for GO terms, KEGG, Biocarta, Pathway Interaction Database, and Reactome. Additionally, it dynamically links to gnomAD for variant information and incorporates ClinVar data for pathogenic variant information. VGC supports the Human Genome Assembly Hg37 and Hg38, ensuring compatibility with a wide range of data sets, and accommodates various approaches to exploring genetic variation data. It can be tailored to specific user needs with optional phenotype input data.
In summary, VGC provides a comprehensive set of features tailored to researchers working with genomic variation data. Its intuitive interface, rapid filtering capabilities, and the flexibility to perform queries using custom groups make it an effective tool in identifying variants potentially associated with diseases. VGC operates locally, ensuring data security and privacy by eliminating the need for cloud-based VCF uploads, making it a secure and user-friendly tool. It is freely available at https://github.com/alperuzun/VGC .
变体调用格式（VCF）文件是一种结构化且全面的文本文件，对于研究人员和临床医生来说，它是解释和理解基因组变异数据的关键。它包含有关基因组中变体位置的重要信息，以及等位基因、基因型调用和质量分数。然而，由于需要各种资源和强大的功能来深入探索，分析和可视化这些文件具有很大的挑战性。
为了解决这些挑战，我们引入了变体图工艺（VGC），这是一种 VCF 文件可视化和分析工具。VGC 提供了广泛的功能来探索遗传变异，包括变体数据的提取、直观的可视化以及带有基因型信息的样本的图形表示。VGC 主要设计用于分析患者队列，但也可以适应个体先证者或家族的分析。它与外部资源无缝集成，提供了对样本数据中基因功能和变异频率的深入了解。VGC 包括来自分子特征数据库（MSigDB）的基因功能和通路信息，用于 GO 术语、KEGG、Biocarta、通路相互作用数据库和 Reactome。此外，它还动态链接到 gnomAD 以获取变体信息，并包含 ClinVar 数据以获取致病性变体信息。VGC 支持人类基因组组装 Hg37 和 Hg38，确保与广泛的数据集兼容，并适应各种探索遗传变异数据的方法。它可以根据用户的具体需求进行定制，带有可选的表型输入数据。
总之，VGC 为处理基因组变异数据的研究人员提供了一套全面的功能。它的直观界面、快速过滤功能以及使用自定义组进行查询的灵活性，使其成为识别可能与疾病相关的变体的有效工具。VGC 在本地运行，通过消除对基于云的 VCF 上传的需求，确保数据安全和隐私，使其成为一种安全且用户友好的工具。它可以在 https://github.com/alperuzun/VGC 上免费获得。
