TY - JOUR
T1 - MANTA, an integrative database and analysis platform that relates microbiome and phenotypic data
AU - Chen, Yi An
AU - Park, Jonguk
AU - Natsume-Kitatani, Yayoi
AU - Kawashima, Hitoshi
AU - Mohsen, Attayeb
AU - Hosomi, Koji
AU - Tanisawa, Kumpei
AU - Ohno, Harumi
AU - Konishi, Kana
AU - Murakami, Haruka
AU - Miyachi, Motohiko
AU - Kunisawa, Jun
AU - Mizuguchi, Kenji
N1 - Funding Information:
This work was supported by the Japan Society for the Promotion of Science under grant numbers 17K07268 (K.M.), 18H02150 (J.K.), 18H02674 (J.K.), 17K09604 (J.K.), and 18K17997 (K.H.); the Japan Agency for Medical Research and Development (AMED) under grant numbers 17fk0108223h0002 (J.K.), 17ek0410032s0102 (J. K.), 17fk0108207h0002 (J.K.), 17ek0210078h0002 (J.K.), 17ak0101068h0001 (J.K.), 17gm1010006s0101 (J.K.), and 18ck0106243h0003 (J.K.); the Ministry of Health, Labour and Welfare of Japan under grant number 15654110 (M.M.); the ONO Medical Research Foundation (J.K.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank the members in the Mizuguchi lab for the critical reading of the manuscript.
Publisher Copyright:
© 2020 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020/12
Y1 - 2020/12
N2 - 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.
AB - 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.
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U2 - 10.1371/journal.pone.0243609
DO - 10.1371/journal.pone.0243609
M3 - Article
C2 - 33275647
AN - SCOPUS:85097310642
SN - 1932-6203
VL - 15
JO - PloS one
JF - PloS one
IS - 12 December
M1 - e0243609
ER -