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Article: Parallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms
Title | Parallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms |
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Authors | |
Keywords | Microbiome Multiplatform Parallel computing Visualization Workflow |
Issue Date | 2022 |
Publisher | John 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? |
Abstract | Massive 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 Identifier | http://hdl.handle.net/10722/311260 |
ISSN | 2023 Impact Factor: 23.7 2023 SCImago Journal Rankings: 3.269 |
DC Field | Value | Language |
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dc.contributor.author | Chen, Y | - |
dc.contributor.author | Li, J | - |
dc.contributor.author | Zhang, Y | - |
dc.contributor.author | Zhang, M | - |
dc.contributor.author | Sun, Z | - |
dc.contributor.author | Jing, G | - |
dc.contributor.author | Huang, S | - |
dc.contributor.author | Su, X | - |
dc.date.accessioned | 2022-03-21T08:47:09Z | - |
dc.date.available | 2022-03-21T08:47:09Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | iMeta, 2022, v. 1 n. 1, article no. e1 | - |
dc.identifier.issn | 2770-596X | - |
dc.identifier.uri | http://hdl.handle.net/10722/311260 | - |
dc.description.abstract | Massive 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.language | eng | - |
dc.publisher | John Wiley & Sons. The Journal's web site is located at https://onlinelibrary.wiley.com/journal/2770596x | - |
dc.relation.ispartof | iMeta | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Microbiome | - |
dc.subject | Multiplatform | - |
dc.subject | Parallel computing | - |
dc.subject | Visualization | - |
dc.subject | Workflow | - |
dc.title | Parallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms | - |
dc.type | Article | - |
dc.identifier.email | Huang, S: shihuang@hku.hk | - |
dc.identifier.authority | Huang, S=rp02929 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1002/imt2.1 | - |
dc.identifier.hkuros | 332145 | - |
dc.identifier.volume | 1 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | article no. e1 | - |
dc.identifier.epage | article no. e1 | - |
dc.publisher.place | Australia | - |