happi:一种层次化的泛基因组推断方法。

happi: a hierarchical approach to pangenomics inference.

机构信息

Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA, USA.

Department of Biostatistics, University of Washington, Seattle, WA, USA.

出版信息

Genome Biol. 2023 Sep 29;24(1):214. doi: 10.1186/s13059-023-03040-6.

Abstract

Recovering metagenome-assembled genomes (MAGs) from shotgun sequencing data is an increasingly common task in microbiome studies, as MAGs provide deeper insight into the functional potential of both culturable and non-culturable microorganisms. However, metagenome-assembled genomes vary in quality and may contain omissions and contamination. These errors present challenges for detecting genes and comparing gene enrichment across sample types. To address this, we propose happi, an approach to testing hypotheses about gene enrichment that accounts for genome quality. We illustrate the advantages of happi over existing approaches using published Saccharibacteria MAGs, Streptococcus thermophilus MAGs, and via simulation.

摘要

从鸟枪法测序数据中恢复宏基因组组装基因组(MAG)是微生物组研究中越来越常见的任务,因为 MAG 提供了对可培养和不可培养微生物的功能潜力的更深入了解。然而,宏基因组组装基因组的质量各不相同,可能存在遗漏和污染。这些错误给检测基因和比较不同样本类型的基因丰度带来了挑战。为了解决这个问题,我们提出了 happi,这是一种针对基因丰度的假设检验方法,考虑了基因组的质量。我们使用已发表的 Saccharibacteria MAG、Streptococcus thermophilus MAG 和模拟数据说明了 happi 相对于现有方法的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21fd/10540326/6c1881389d6d/13059_2023_3040_Fig1_HTML.jpg

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