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Article: Parallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms

TitleParallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms
Authors
KeywordsMicrobiome
Multiplatform
Parallel computing
Visualization
Workflow
Issue Date2022
PublisherJohn Wiley & Sons. The Journal's web site is located at https://onlinelibrary.wiley.com/journal/2770596x
Citation
iMeta, 2022, v. 1 n. 1, article no. e1 How to Cite?
AbstractMassive microbiome sequencing data has been generated, which elucidates associations between microbes and their environmental phenotypes such as host health or ecosystem status. Outstanding bioinformatic tools are the basis to decipher the biological information hidden under microbiome data. However, most approaches placed difficulties on the accessibility to nonprofessional users. On the other side, the computing throughput has become a significant bottleneck of many analytical pipelines in processing large-scale datasets. In this study, we introduce Parallel-Meta Suite (PMS), an interactive software package for fast and comprehensive microbiome data analysis, visualization, and interpretation. It covers a wide array of functions for data preprocessing, statistics, visualization by state-of-the-art algorithms in a user-friendly graphical interface, which is accessible to diverse users. To meet the rapidly increasing computational demands, the entire procedure of PMS has been optimized by a parallel computing scheme, enabling the rapid processing of thousands of samples. PMS is compatible with multiple platforms, and an installer has been integrated for full-automatic installation.
Persistent Identifierhttp://hdl.handle.net/10722/311260
ISSN

 

DC FieldValueLanguage
dc.contributor.authorChen, Y-
dc.contributor.authorLi, J-
dc.contributor.authorZhang, Y-
dc.contributor.authorZhang, M-
dc.contributor.authorSun, Z-
dc.contributor.authorJing, G-
dc.contributor.authorHuang, S-
dc.contributor.authorSu, X-
dc.date.accessioned2022-03-21T08:47:09Z-
dc.date.available2022-03-21T08:47:09Z-
dc.date.issued2022-
dc.identifier.citationiMeta, 2022, v. 1 n. 1, article no. e1-
dc.identifier.issn2770-596X-
dc.identifier.urihttp://hdl.handle.net/10722/311260-
dc.description.abstractMassive microbiome sequencing data has been generated, which elucidates associations between microbes and their environmental phenotypes such as host health or ecosystem status. Outstanding bioinformatic tools are the basis to decipher the biological information hidden under microbiome data. However, most approaches placed difficulties on the accessibility to nonprofessional users. On the other side, the computing throughput has become a significant bottleneck of many analytical pipelines in processing large-scale datasets. In this study, we introduce Parallel-Meta Suite (PMS), an interactive software package for fast and comprehensive microbiome data analysis, visualization, and interpretation. It covers a wide array of functions for data preprocessing, statistics, visualization by state-of-the-art algorithms in a user-friendly graphical interface, which is accessible to diverse users. To meet the rapidly increasing computational demands, the entire procedure of PMS has been optimized by a parallel computing scheme, enabling the rapid processing of thousands of samples. PMS is compatible with multiple platforms, and an installer has been integrated for full-automatic installation.-
dc.languageeng-
dc.publisherJohn Wiley & Sons. The Journal's web site is located at https://onlinelibrary.wiley.com/journal/2770596x-
dc.relation.ispartofiMeta-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectMicrobiome-
dc.subjectMultiplatform-
dc.subjectParallel computing-
dc.subjectVisualization-
dc.subjectWorkflow-
dc.titleParallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms-
dc.typeArticle-
dc.identifier.emailHuang, S: shihuang@hku.hk-
dc.identifier.authorityHuang, S=rp02929-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1002/imt2.1-
dc.identifier.hkuros332145-
dc.identifier.volume1-
dc.identifier.issue1-
dc.identifier.spagearticle no. e1-
dc.identifier.epagearticle no. e1-
dc.publisher.placeAustralia-

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