塔达:对分类学有意识的数据集聚合器
Emil Hägglund1, Siv G E Andersson1, Lionel Guy2
1Molecular Evolution, Department of Cell and Molecular Biology, Science for Life Laboratory, Biomedical Centre, Uppsala University, SE-751 24 Uppsala, Sweden.
Bioinformatics (Oxford, England)
|December 7, 2023
概括
选择代表性基因组用于细菌和考古物种遗传学分析至关重要. TADA (分类学意识数据集选择) 是一个新的工作流程,可以自动化这一过程,确保基因组数据集的质量和多样性.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 进化生物学 进化生物学
背景情况:
- 越来越多的细菌和古人类基因组的测序使得先进的遗传学和比较基因组研究成为可能.
- 然而,利用所有可用的基因组数据进行遗传遗传重建是计算上具有挑战性的,并且可以引入因多样性分布不均的偏差而导致的偏差.
研究的目的:
- 开发一种用户友好的软件解决方案,以高效,可靠地对 prokaryotic 基因组进行子样本采集,以进行基因组学分析.
- 在大规模基因组研究中解决对自动分类学意识数据集选择的需求.
主要方法:
- 实现TADA作为一个Snakemake工作流程.
- 开发一种具有分类学意识的数据集选择过程,具有可调节的细分度.
- 包括基因组质量控制和分支平衡参数.
主要成果:
- 塔达有助于从各种 prokaryotic 血统中选择具有代表性的基因组子集.
- 工作流允许用户定义的样本采集策略跨 prokaryotic 多样性.
- 对基因组质量和家族遗传平衡的限制被整合到选择过程中.
结论:
- 塔达为构建高质量,多样化的基因组数据集以进行遗传学推断提供了一种实用解决方案.
- 这种工具提高了对 Prokaryotes 进行大规模植物遗传分析的可行性.
- 自动化,分类学意识的亚抽样提高了比较基因组学的效率和准确性.
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