| Autor: |
Yi-An Chen, Jonguk Park, Yayoi Natsume-Kitatani, Hitoshi Kawashima, Attayeb Mohsen, Koji Hosomi, Kumpei Tanisawa, Harumi Ohno, Kana Konishi, Haruka Murakami, Motohiko Miyachi, Jun Kunisawa, Kenji Mizuguchi |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
PLoS ONE, Vol 15, Iss 12, p e0243609 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1932-6203 |
| DOI: |
10.1371/journal.pone.0243609 |
| Popis: |
With an ever-increasing interest in understanding the relationships between the microbiota and the host, more tools to map, analyze and interpret these relationships have been developed. Most of these tools, however, focus on taxonomic profiling and comparative analysis among groups, with very few analytical tools designed to correlate microbiota and the host phenotypic data. We have developed a software program for creating a web-based integrative database and analysis platform called MANTA (Microbiota And pheNoType correlation Analysis platform). In addition to storing the data, MANTA is equipped with an intuitive user interface that can be used to correlate the microbial composition with phenotypic parameters. Using a case study, we demonstrated that MANTA was able to quickly identify the significant correlations between microbial abundances and phenotypes that are supported by previous studies. Moreover, MANTA enabled the users to quick access locally stored data that can help interpret microbiota-phenotype relations. MANTA is available at https://mizuguchilab.org/manta/ for download and the source code can be found at https://github.com/chenyian-nibio/manta. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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