gNOMO2:用于微生物组多组学综合分析的综合模块化管道。

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES GigaScience Pub Date : 2024-01-02 DOI:10.1093/gigascience/giae038
Muzaffer Arikan, Thilo Muth
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引用次数: 0

摘要

背景:近年来,组学技术为深入了解微生物群落的结构和功能特征提供了难得的机会。因此,对用户友好型、可重现性和多功能生物信息学工具的需求与日俱增,这些工具能有效利用多组学数据,提供对微生物组的整体理解。在此之前,我们曾介绍过 gNOMO,这是一种专门为综合分析微生物组多组学数据而定制的生物信息学管道。为了应对微生物组领域不断发展的需求以及综合多组学数据分析日益增长的必要性,我们对 gNOMO 管道进行了大幅改进:结果:在这里,我们介绍了gNOMO2,这是一个全面的模块化管道,可以无缝管理各种组学组合,包括2到4种不同的组学数据类型,包括16S核糖体RNA(rRNA)基因扩增子测序、元基因组学、元转录组学和元蛋白组学。此外,gNOMO2 还有一个专门的模块,用于处理 16S rRNA 基因扩增片段测序数据,创建适合元蛋白质组学研究的蛋白质数据库。此外,它还采用了新的差异丰度、整合和可视化方法,增强了工具包的功能,使微生物组的分析更具洞察力。结论:gNOMO2 能够将微生物组多组学数据中的分类和功能分析彻底整合在一起,为与宿主相关和自由生活的微生物组研究提供新的见解。gNOMO2 可在 https://github.com/muzafferarikan/gNOMO2 免费获取。
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gNOMO2: a comprehensive and modular pipeline for integrated multi-omics analyses of microbiomes.

Background: In recent years, omics technologies have offered an exceptional chance to gain a deeper insight into the structural and functional characteristics of microbial communities. As a result, there is a growing demand for user-friendly, reproducible, and versatile bioinformatic tools that can effectively harness multi-omics data to provide a holistic understanding of microbiomes. Previously, we introduced gNOMO, a bioinformatic pipeline tailored to analyze microbiome multi-omics data in an integrative manner. In response to the evolving demands within the microbiome field and the growing necessity for integrated multi-omics data analysis, we have implemented substantial enhancements to the gNOMO pipeline.

Results: Here, we present gNOMO2, a comprehensive and modular pipeline that can seamlessly manage various omics combinations, ranging from 2 to 4 distinct omics data types, including 16S ribosomal RNA (rRNA) gene amplicon sequencing, metagenomics, metatranscriptomics, and metaproteomics. Furthermore, gNOMO2 features a specialized module for processing 16S rRNA gene amplicon sequencing data to create a protein database suitable for metaproteomics investigations. Moreover, it incorporates new differential abundance, integration, and visualization approaches, enhancing the toolkit for a more insightful analysis of microbiomes. The functionality of these new features is showcased through the use of 4 microbiome multi-omics datasets encompassing various ecosystems and omics combinations. gNOMO2 not only replicated most of the primary findings from these studies but also offered further valuable perspectives.

Conclusions: gNOMO2 enables the thorough integration of taxonomic and functional analyses in microbiome multi-omics data, offering novel insights in both host-associated and free-living microbiome research. gNOMO2 is available freely at https://github.com/muzafferarikan/gNOMO2.

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来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
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