PDF(Pubmed)
Abstract：
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.
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.
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.
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.
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.
摘要：
背景：近年来，组学技术为更深入地了解微生物群落的结构和功能特征提供了绝佳的机会。因此,对用户友好的需求日益增长，可重复,和多功能的生物信息学工具，可以有效地利用多组学数据，提供对微生物的全面理解。以前,我们引入了gNOMO，为以综合方式分析微生物组多组学数据而量身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对集成的多组学数据分析的日益增长的必要性，我们已经对gNOMO管道进行了实质性的增强。
结果：这里，我们提出了gNOMO2，一个全面的模块化管道，可以无缝地管理各种组学组合，范围从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，宏基因组学，metatranscriptomics,和元蛋白质组学。此外，gNOMO2具有专门的模块，用于处理16SrRNA基因扩增子测序数据，以创建适合于元蛋白质组学研究的蛋白质数据库。此外，它包含了新的差异丰度，一体化,和可视化方法，增强工具包，以便对微生物组进行更有见地的分析。通过使用包含各种生态系统和组学组合的4个微生物组多组学数据集，展示了这些新功能的功能。gNOMO2不仅复制了这些研究的大多数主要发现，而且还提供了更多有价值的观点。
结论：gNOMO2能够在微生物组多组数据中彻底整合分类学和功能分析，在宿主相关和自由生活的微生物组研究中提供新的见解。gNOMO2可在https://github.com/muzafferarikan/gNOMO2免费获得。
结果：这里，我们提出了gNOMO2，一个全面的模块化管道，可以无缝地管理各种组学组合，范围从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，宏基因组学，metatranscriptomics,和元蛋白质组学。此外，gNOMO2具有专门的模块，用于处理16SrRNA基因扩增子测序数据，以创建适合于元蛋白质组学研究的蛋白质数据库。此外，它包含了新的差异丰度，一体化,和可视化方法，增强工具包，以便对微生物组进行更有见地的分析。通过使用包含各种生态系统和组学组合的4个微生物组多组学数据集，展示了这些新功能的功能。gNOMO2不仅复制了这些研究的大多数主要发现，而且还提供了更多有价值的观点。
结论：gNOMO2能够在微生物组多组数据中彻底整合分类学和功能分析，在宿主相关和自由生活的微生物组研究中提供新的见解。gNOMO2可在https://github.com/muzafferarikan/gNOMO2免费获得。
