Antonio Parraga-Leo, Tomiko T Oskotsky, Boris Oskotsky, Camilla Wibrand, Alennie Roldan, Alice S Tang, Connie W Y Ha, Ronald J Wong, Samuel S Minot, Gaia Andreoletti, Idit Kosti, Kevin R Theis, Sherrianne Ng, Yun S Lee, Patricia Diaz-Gimeno, Phillip R Bennett, David A MacIntyre, Susan V Lynch, Roberto Romero, Adi L Tarca, David K Stevenson, Nima Aghaeepour, Jonathan L Golob, Marina Sirota
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引用次数: 0
摘要
目的实现孕期阴道微生物组的交互式可视化，促进新见解的发现和新假设的产生：妊娠期阴道微生物组图谱（VMAP）由R shiny创建，可对多项研究中的结构化阴道微生物组数据进行可视化：VMAP（http://vmapapp.org）可视化了来自11项研究的1402名孕妇的3880份阴道微生物组样本，这些样本通过开源工具MaLiAmPi汇总。可视化特征包括多样性测量、VALENCIA群落状态类型和组成（系统型、分类学），可按不同类别进行筛选：这项工作代表了迄今为止规模最大、地理位置最多样化的妊娠期阴道微生物群集合之一，是进一步分析阴道微生物群数据和更好地了解妊娠及相关结果的用户友好型资源：VMAP 可从 https://github.com/msirota/vmap.git 获取，目前已作为在线应用程序部署给非 R 用户。
Objectives: To enable interactive visualization of the vaginal microbiome across the pregnancy and facilitate discovery of novel insights and generation of new hypotheses.
Material and methods: Vaginal Microbiome Atlas during Pregnancy (VMAP) was created with R shiny to generate visualizations of structured vaginal microbiome data from multiple studies.
Results: VMAP (http://vmapapp.org) visualizes 3880 vaginal microbiome samples of 1402 pregnant individuals from 11 studies, aggregated via open-source tool MaLiAmPi. Visualized features include diversity measures, VALENCIA community state types, and composition (phylotypes, taxonomy) that can be filtered by various categories.
Discussion: This work represents one of the largest and most geographically diverse aggregations of the vaginal microbiome in pregnancy to date and serves as a user-friendly resource to further analyze vaginal microbiome data and better understand pregnancies and associated outcomes.
Conclusion: VMAP can be obtained from https://github.com/msirota/vmap.git and is currently deployed as an online app for non-R users.
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