DivBrowse—interactive visualization and exploratory data analysis of variant call matrices

Author:

König Patrick1ORCID,Beier Sebastian12ORCID,Mascher Martin34ORCID,Stein Nils35ORCID,Lange Matthias1ORCID,Scholz Uwe1ORCID

Affiliation:

1. Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben , 06466 Seeland , Germany

2. Institute of Bio- and Geosciences, IBG-4, Forschungszentrum Jülich GmbH , 52425 Jülich , Germany

3. Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben , 06466 Seeland , Germany

4. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig , 04103 Leipzig , Germany

5. Center for Integrated Breeding Research, Georg-August University , 37075 Göttingen , Germany

Abstract

Abstract Background The sequencing of whole genomes is becoming increasingly affordable. In this context, large-scale sequencing projects are generating ever larger datasets of species-specific genomic diversity. As a consequence, more and more genomic data need to be made easily accessible and analyzable to the scientific community. Findings We present DivBrowse, a web application for interactive visualization and exploratory analysis of genomic diversity data stored in Variant Call Format (VCF) files of any size. By seamlessly combining BLAST as an entry point together with interactive data analysis features such as principal component analysis in one graphical user interface, DivBrowse provides a novel and unique set of exploratory data analysis capabilities for genomic biodiversity datasets. The capability to integrate DivBrowse into existing web applications supports interoperability between different web applications. Built-in interactive computation of principal component analysis allows users to perform ad hoc analysis of the population structure based on specific genetic elements such as genes and exons. Data interoperability is supported by the ability to export genomic diversity data in VCF and General Feature Format 3 files. Conclusion DivBrowse offers a novel approach for interactive visualization and analysis of genomic diversity data and optionally also gene annotation data by including features like interactive calculation of variant frequencies and principal component analysis. The use of established standard file formats for data input supports interoperability and seamless deployment of application instances based on the data output of established bioinformatics pipelines.

Funder

Leibniz-Gemeinschaft

Pakt für Forschung und Innovation

Bundesministerium für Bildung und Frauen

Deutsche Forschungsgemeinschaft

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Cultivating Customer Purchase Intent: Leveraging Machine Learning for Precise Predictions;2023 12th International Conference on System Modeling & Advancement in Research Trends (SMART);2023-12-22

2. Correction to: DivBrowse—interactive visualization and exploratory data analysis of variant call matrices;GigaScience;2022-12-28

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