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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Abstract
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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