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MRMkit: Automated Data Processing for Large-Scale Targeted Metabolomics Analysis.
Teo, Guoshou; Chew, Wee Siong; Burla, Bo J; Herr, Deron; Tai, E Shyong; Wenk, Markus R; Torta, Federico; Choi, Hyungwon.
Affiliation
  • Teo G; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, 1E, Kent Ridge Road, NUHS Tower Block, Level 10, Singapore 119228.
  • Chew WS; Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD3, 16 Medical Drive, Level 4, #04-01, Singapore 117600.
  • Burla BJ; Singapore Lipidomics Incubator, Life Science Institute, National University of Singapore, 28 Medical Drive, Singapore 117456.
  • Herr D; Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Block MD3, 16 Medical Drive, Level 4, #04-01, Singapore 117600.
  • Tai ES; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, 1E, Kent Ridge Road, NUHS Tower Block, Level 10, Singapore 119228.
  • Wenk MR; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Block MD7, 8 Medical Drive, Singapore 117596.
  • Torta F; Singapore Lipidomics Incubator, Life Science Institute, National University of Singapore, 28 Medical Drive, Singapore 117456.
  • Choi H; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Block MD7, 8 Medical Drive, Singapore 117596.
Anal Chem ; 92(20): 13677-13682, 2020 10 20.
Article in En | MEDLINE | ID: mdl-32930575
ABSTRACT
MRMkit is an open-source software package designed for automated processing of large-scale targeted mass spectrometry-based metabolomics data. With improvements in the automation of sample preparation for LC-MS analysis, a challenging next step is to fully automate the workflow to process raw data and ensure the quality of measurements in large-scale analysis settings. MRMkit capitalizes on the richness of large-sample data in capturing peak shapes and interference patterns of transitions across many samples and delivers fully automated, reproducible peak integration results in a scalable and time-efficient manner. In addition to fast and accurate peak integration, the tool also provides reliable data normalization functions and quality metrics along with visualizations for fast data quality evaluation. In addition, MRMkit learns retention time offset patterns by user-specified compound classes and makes recommendations for peak picking in multimodal ion chromatograms. In summary, MRMkit offers highly consistent and scalable data processing capacity for targeted metabolomics, substantially curtailing the time required to produce the final quantification results after LC-MS analysis.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: User-Computer Interface / Metabolomics Language: En Journal: Anal Chem Year: 2020 Type: Article

Full text: 1 Database: MEDLINE Main subject: User-Computer Interface / Metabolomics Language: En Journal: Anal Chem Year: 2020 Type: Article