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Fast-GBS v2.0:一款用于测序数据基因型分析的工具包。

Fast-GBS v2.0: an analysis toolkit for genotyping-by-sequencing data.

机构信息

Département de Phytologie, Université Laval, Québec City, QC, Canada.

Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, QC, Canada.

出版信息

Genome. 2020 Nov;63(11):577-581. doi: 10.1139/gen-2020-0077. Epub 2020 Oct 2.

Abstract

Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support. Here, we present the second generation of Fast-GBS (v2.0) that offers several new options (e.g., processing paired-end reads and imputation of missing data) and features (e.g., summary statistics of genotypes) to improve the GBS data analysis process. The performance assessment analysis showed that Fast-GBS v2.0 outperformed other available analytical pipelines, such as GBS-SNP-CROP and Gb-eaSy. Fast-GBS v2.0 provides an analysis platform that can be run with different types of sequencing data, modest computational resources, and allows for missing-data imputation for various species in different contexts.

摘要

测序基因型分析(GBS)是一种快速、灵活、低成本且强大的基因分型方法,可同时在广泛的样本范围内发现变体并进行基因型分析。这些特点使得 GBS 成为从保护生物学到模型和非模型物种的功能基因组学等许多应用和研究问题的绝佳工具。GBS 的持续改进依赖于对数据分析的更全面理解、快速高效的生物信息学管道的开发、准确的缺失数据插补以及积极的发布后支持。在这里,我们提出了第二代 Fast-GBS(v2.0),它提供了几个新的选项(例如,处理配对末端读取和缺失数据的插补)和功能(例如,基因型的汇总统计信息),以改进 GBS 数据分析过程。性能评估分析表明,Fast-GBS v2.0 优于其他可用的分析管道,如 GBS-SNP-CROP 和 Gb-eaSy。Fast-GBS v2.0 提供了一个分析平台,可用于不同类型的测序数据,适度的计算资源,并允许在不同情况下对各种物种进行缺失数据插补。

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