MetaOmics：用于转录组元分析的分析管道和基于浏览器的软件套件。
MetaOmics: analysis pipeline and browser-based software suite for transcriptomic meta-analysis.
机构信息
Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD, USA.
Department of Biostatistics, University of Florida, Gainesville, FL, USA.
出版信息
Bioinformatics. 2019 May 1;35(9):1597-1599. doi: 10.1093/bioinformatics/bty825.
SUMMARY
The rapid advances of omics technologies have generated abundant genomic data in public repositories and effective analytical approaches are critical to fully decipher biological knowledge inside these data. Meta-analysis combines multiple studies of a related hypothesis to improve statistical power, accuracy and reproducibility beyond individual study analysis. To date, many transcriptomic meta-analysis methods have been developed, yet few thoughtful guidelines exist. Here, we introduce a comprehensive analytical pipeline and browser-based software suite, called MetaOmics, to meta-analyze multiple transcriptomic studies for various biological purposes, including quality control, differential expression analysis, pathway enrichment analysis, differential co-expression network analysis, prediction, clustering and dimension reduction. The pipeline includes many public as well as >10 in-house transcriptomic meta-analytic methods with data-driven and biological-aim-driven strategies, hands-on protocols, an intuitive user interface and step-by-step instructions.
AVAILABILITY AND IMPLEMENTATION
MetaOmics is freely available at https://github.com/metaOmics/metaOmics.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
组学技术的快速发展已经在公共存储库中产生了大量的基因组数据，而有效的分析方法对于充分破译这些数据中的生物学知识至关重要。元分析将多个相关假设的研究结合起来，以提高统计能力、准确性和可重复性，超越了单个研究分析。迄今为止，已经开发了许多转录组元分析方法，但很少有深思熟虑的指南。在这里，我们介绍了一个全面的分析管道和基于浏览器的软件套件，称为 MetaOmics，用于元分析多个转录组研究，用于各种生物学目的，包括质量控制、差异表达分析、途径富集分析、差异共表达网络分析、预测、聚类和降维。该管道包括许多公共的和 10 多个内部转录组元分析方法，具有数据驱动和生物学目标驱动的策略、实践协议、直观的用户界面和逐步说明。
可用性和实现
MetaOmics 可在 https://github.com/metaOmics/metaOmics 上免费获得。
补充信息
补充数据可在生物信息学在线获得。
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