Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhengjiang 310052, China.
Department of Epidemiology and Health Statistics, Zhejiang University School of Public Health, Hangzhou, Zhengjiang 310058, China.
Bioinformatics. 2023 Dec 1;39(12). doi: 10.1093/bioinformatics/btad715.
MOTIVATION: Gut dysbiosis is closely associated with obesity and related metabolic diseases including type 2 diabetes (T2D) and nonalcoholic fatty liver disease (NAFLD). The gut microbial features and biomarkers have been increasingly investigated in many studies, which require further validation due to the limited sample size and various confounding factors that may affect microbial compositions in a single study. So far, it lacks a comprehensive bioinformatics pipeline providing automated statistical analysis and integrating multiple independent studies for cross-validation simultaneously. RESULTS: OBMeta aims to streamline the standard metagenomics data analysis from diversity analysis, comparative analysis, and functional analysis to co-abundance network analysis. In addition, a curated database has been established with a total of 90 public research projects, covering three different phenotypes (Obesity, T2D, and NAFLD) and more than five different intervention strategies (exercise, diet, probiotics, medication, and surgery). With OBMeta, users can not only analyze their research projects but also search and match public datasets for cross-validation. Moreover, OBMeta provides cross-phenotype and cross-intervention-based advanced validation that maximally supports preliminary findings from an individual study. To summarize, OBMeta is a comprehensive web server to analyze and validate gut microbial features and biomarkers for obesity-associated metabolic diseases. AVAILABILITY AND IMPLEMENTATION: OBMeta is freely available at: http://obmeta.met-bioinformatics.cn/.
动机:肠道菌群失调与肥胖及相关代谢性疾病密切相关,包括 2 型糖尿病(T2D)和非酒精性脂肪性肝病(NAFLD)。许多研究越来越关注肠道微生物特征和生物标志物,但由于样本量有限以及可能影响单个研究中微生物组成的各种混杂因素,这些研究结果需要进一步验证。到目前为止,还缺乏一个全面的生物信息学分析管道,该管道能够提供自动化的统计分析,并同时整合多个独立的研究进行交叉验证。
结果:OBMeta 的目的是简化从多样性分析、比较分析和功能分析到共丰度网络分析的标准宏基因组数据分析流程。此外,还建立了一个经过精心整理的数据库,其中包含 90 个公共研究项目,涵盖三种不同表型(肥胖、T2D 和 NAFLD)和五种不同的干预策略(运动、饮食、益生菌、药物和手术)。使用 OBMeta,用户不仅可以分析自己的研究项目,还可以搜索和匹配公共数据集进行交叉验证。此外,OBMeta 还提供基于跨表型和跨干预的高级验证,最大限度地支持从个体研究中获得的初步发现。总之,OBMeta 是一个用于分析和验证与肥胖相关代谢性疾病相关的肠道微生物特征和生物标志物的综合网络服务器。
可用性和实现:OBMeta 可免费使用:http://obmeta.met-bioinformatics.cn/。
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