Hashimoto Shumpei
Laboratory of Plant Breeding and Genetics, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
Breed Sci. 2024 Dec;74(5):454-461. doi: 10.1270/jsbbs.24041. Epub 2024 Nov 23.
Visualizing genotypic data is essential in genetic research and breeding programs as it offers clear representations of genomic information, enhancing understanding of genetic architecture. This becomes especially critical with the emergence of next-generation sequencing (NGS) technologies, which generate vast datasets necessitating effective visualization tools. While traditional tools for graphical genotypes have been groundbreaking, they often lack flexibility and universal applicability. These tools encounter limitations such as user-customized visualization and compatibility issues across different operating systems. In this study, I introduce GenoSee, a novel visualization tool designed to address these shortcomings. GenoSee can handle phased and non-phased variant calling data, offering extensive customization to suit diverse research requirements. It operates seamlessly across multiple platforms, ensuring compatibility, and provides high-quality graphical genotypes. GenoSee facilitates deeper insights into genomic structures, thereby advancing genetic and genomic research, and breeding programs by enhancing accessibility to genetic data visualization.
在遗传研究和育种计划中,可视化基因型数据至关重要,因为它能清晰呈现基因组信息,增进对遗传结构的理解。随着下一代测序(NGS)技术的出现,这一点变得尤为关键,这些技术产生了海量数据集,需要有效的可视化工具。虽然传统的图形化基因型工具具有开创性,但它们往往缺乏灵活性和普遍适用性。这些工具存在诸如用户定制可视化以及跨不同操作系统的兼容性问题等局限性。在本研究中,我介绍了GenoSee,这是一种旨在解决这些缺点的新型可视化工具。GenoSee可以处理分阶段和非分阶段的变异调用数据,提供广泛的定制以满足多样化的研究需求。它能在多个平台上无缝运行,确保兼容性,并提供高质量的图形化基因型。GenoSee有助于更深入地洞察基因组结构,从而通过增强对遗传数据可视化的可及性来推进遗传和基因组研究以及育种计划。