IP4M: an integrated platform for mass spectrometry-based metabolomics data mining
Abstract Background Metabolomics data analyses rely on the use of bioinformatics tools. Many integrated multi-functional tools have been developed for untargeted metabolomics data processing and have been widely used. More alternative platforms are expected for both basic and advanced users. Results...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2020-10-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-020-03786-x |
| _version_ | 1818978888559099904 |
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| author | Dandan Liang Quan Liu Kejun Zhou Wei Jia Guoxiang Xie Tianlu Chen |
| author_facet | Dandan Liang Quan Liu Kejun Zhou Wei Jia Guoxiang Xie Tianlu Chen |
| author_sort | Dandan Liang |
| collection | DOAJ |
| description | Abstract Background Metabolomics data analyses rely on the use of bioinformatics tools. Many integrated multi-functional tools have been developed for untargeted metabolomics data processing and have been widely used. More alternative platforms are expected for both basic and advanced users. Results Integrated mass spectrometry-based untargeted metabolomics data mining (IP4M) software was designed and developed. The IP4M, has 62 functions categorized into 8 modules, covering all the steps of metabolomics data mining, including raw data preprocessing (alignment, peak de-convolution, peak picking, and isotope filtering), peak annotation, peak table preprocessing, basic statistical description, classification and biomarker detection, correlation analysis, cluster and sub-cluster analysis, regression analysis, ROC analysis, pathway and enrichment analysis, and sample size and power analysis. Additionally, a KEGG-derived metabolic reaction database was embedded and a series of ratio variables (product/substrate) can be generated with enlarged information on enzyme activity. A new method, GRaMM, for correlation analysis between metabolome and microbiome data was also provided. IP4M provides both a number of parameters for customized and refined analysis (for expert users), as well as 4 simplified workflows with few key parameters (for beginners who are unfamiliar with computational metabolomics). The performance of IP4M was evaluated and compared with existing computational platforms using 2 data sets derived from standards mixture and 2 data sets derived from serum samples, from GC–MS and LC–MS respectively. Conclusion IP4M is powerful, modularized, customizable and easy-to-use. It is a good choice for metabolomics data processing and analysis. Free versions for Windows, MAC OS, and Linux systems are provided. |
| first_indexed | 2024-12-20T16:50:48Z |
| format | Article |
| id | doaj.art-480416fc4b014fbd951b6e9f2f7c7881 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-20T16:50:48Z |
| publishDate | 2020-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-480416fc4b014fbd951b6e9f2f7c78812022-12-21T19:32:50ZengBMCBMC Bioinformatics1471-21052020-10-0121111610.1186/s12859-020-03786-xIP4M: an integrated platform for mass spectrometry-based metabolomics data miningDandan Liang0Quan Liu1Kejun Zhou2Wei Jia3Guoxiang Xie4Tianlu Chen5Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s HospitalHuman Metabolomics Institute, Inc.Human Metabolomics Institute, Inc.Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s HospitalHuman Metabolomics Institute, Inc.Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s HospitalAbstract Background Metabolomics data analyses rely on the use of bioinformatics tools. Many integrated multi-functional tools have been developed for untargeted metabolomics data processing and have been widely used. More alternative platforms are expected for both basic and advanced users. Results Integrated mass spectrometry-based untargeted metabolomics data mining (IP4M) software was designed and developed. The IP4M, has 62 functions categorized into 8 modules, covering all the steps of metabolomics data mining, including raw data preprocessing (alignment, peak de-convolution, peak picking, and isotope filtering), peak annotation, peak table preprocessing, basic statistical description, classification and biomarker detection, correlation analysis, cluster and sub-cluster analysis, regression analysis, ROC analysis, pathway and enrichment analysis, and sample size and power analysis. Additionally, a KEGG-derived metabolic reaction database was embedded and a series of ratio variables (product/substrate) can be generated with enlarged information on enzyme activity. A new method, GRaMM, for correlation analysis between metabolome and microbiome data was also provided. IP4M provides both a number of parameters for customized and refined analysis (for expert users), as well as 4 simplified workflows with few key parameters (for beginners who are unfamiliar with computational metabolomics). The performance of IP4M was evaluated and compared with existing computational platforms using 2 data sets derived from standards mixture and 2 data sets derived from serum samples, from GC–MS and LC–MS respectively. Conclusion IP4M is powerful, modularized, customizable and easy-to-use. It is a good choice for metabolomics data processing and analysis. Free versions for Windows, MAC OS, and Linux systems are provided.http://link.springer.com/article/10.1186/s12859-020-03786-xMetabolomicsData analysisWorkflowSoftware |
| spellingShingle | Dandan Liang Quan Liu Kejun Zhou Wei Jia Guoxiang Xie Tianlu Chen IP4M: an integrated platform for mass spectrometry-based metabolomics data mining BMC Bioinformatics Metabolomics Data analysis Workflow Software |
| title | IP4M: an integrated platform for mass spectrometry-based metabolomics data mining |
| title_full | IP4M: an integrated platform for mass spectrometry-based metabolomics data mining |
| title_fullStr | IP4M: an integrated platform for mass spectrometry-based metabolomics data mining |
| title_full_unstemmed | IP4M: an integrated platform for mass spectrometry-based metabolomics data mining |
| title_short | IP4M: an integrated platform for mass spectrometry-based metabolomics data mining |
| title_sort | ip4m an integrated platform for mass spectrometry based metabolomics data mining |
| topic | Metabolomics Data analysis Workflow Software |
| url | http://link.springer.com/article/10.1186/s12859-020-03786-x |
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