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Article: 3MCor: An integrative web server for metabolome-microbiome-metadata correlation analysis

Title3MCor: An integrative web server for metabolome-microbiome-metadata correlation analysis
Authors
Issue Date2022
Citation
Bioinformatics, 2022, v. 38, n. 5, p. 1378-1384 How to Cite?
AbstractMotivation: The metabolome and microbiome disorders are highly associated with human health, and there are great demands for dual-omics interaction analysis. Here, we designed and developed an integrative platform, 3MCor, for metabolome and microbiome correlation analysis under the instruction of phenotype and with the consideration of confounders. Results: Many traditional and novel correlation analysis methods were integrated for intra- and inter-correlation analysis. Three inter-correlation pipelines are provided for global, hierarchical and pairwise analysis. The incorporated network analysis function is conducive to rapid identification of network clusters and key nodes from a complicated correlation network. Complete numerical results (csv files) and rich figures (pdf files) will be generated in minutes. To our knowledge, 3MCor is the first platform developed specifically for the correlation analysis of metabolome and microbiome. Its functions were compared with corresponding modules of existing omics data analysis platforms. A real-world dataset was used to demonstrate its simple and flexible operation, comprehensive outputs and distinctive contribution to dual-omics studies. Availabilityand implementation: 3MCor is available at http://3mcor.cn and the backend R script is available at https://github.com/chentianlu/3MCorServer.
Persistent Identifierhttp://hdl.handle.net/10722/342644
ISSN
2023 Impact Factor: 4.4
2023 SCImago Journal Rankings: 2.574
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorSun, Tao-
dc.contributor.authorLi, Mengci-
dc.contributor.authorYu, Xiangtian-
dc.contributor.authorLiang, Dandan-
dc.contributor.authorXie, Guoxiang-
dc.contributor.authorSang, Chao-
dc.contributor.authorJia, Wei-
dc.contributor.authorChen, Tianlu-
dc.date.accessioned2024-04-17T07:05:15Z-
dc.date.available2024-04-17T07:05:15Z-
dc.date.issued2022-
dc.identifier.citationBioinformatics, 2022, v. 38, n. 5, p. 1378-1384-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/342644-
dc.description.abstractMotivation: The metabolome and microbiome disorders are highly associated with human health, and there are great demands for dual-omics interaction analysis. Here, we designed and developed an integrative platform, 3MCor, for metabolome and microbiome correlation analysis under the instruction of phenotype and with the consideration of confounders. Results: Many traditional and novel correlation analysis methods were integrated for intra- and inter-correlation analysis. Three inter-correlation pipelines are provided for global, hierarchical and pairwise analysis. The incorporated network analysis function is conducive to rapid identification of network clusters and key nodes from a complicated correlation network. Complete numerical results (csv files) and rich figures (pdf files) will be generated in minutes. To our knowledge, 3MCor is the first platform developed specifically for the correlation analysis of metabolome and microbiome. Its functions were compared with corresponding modules of existing omics data analysis platforms. A real-world dataset was used to demonstrate its simple and flexible operation, comprehensive outputs and distinctive contribution to dual-omics studies. Availabilityand implementation: 3MCor is available at http://3mcor.cn and the backend R script is available at https://github.com/chentianlu/3MCorServer.-
dc.languageeng-
dc.relation.ispartofBioinformatics-
dc.title3MCor: An integrative web server for metabolome-microbiome-metadata correlation analysis-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/bioinformatics/btab818-
dc.identifier.pmid34874987-
dc.identifier.scopuseid_2-s2.0-85125461516-
dc.identifier.volume38-
dc.identifier.issue5-
dc.identifier.spage1378-
dc.identifier.epage1384-
dc.identifier.eissn1460-2059-
dc.identifier.isiWOS:000776280200025-

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