Summary of Study ST001493
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001011. The data can be accessed directly via it's Project DOI: 10.21228/M8111X This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
Study ID | ST001493 |
Study Title | Dynamic binning peak detection and assessment of various lipidomics liquid chromatography-mass spectrometry pre-processing platforms |
Study Summary | Liquid chromatography-mass spectrometry (LC-MS) based lipidomics generate a large dataset, which requires high-performance data pre-processing tools for their interpretation such as XCMS, mzMine and Progenesis. These pre-processing tools rely heavily on accurate peak detection, which depends on setting the peak detection mass tolerance (PDMT) properly. The PDMT is usually set with a fixed value in either ppm or Da units. However, this fixed value may result in duplicates or missed peak detection. Therefore, we developed the dynamic binning method for accurate peak detection, which takes into account the peak broadening described by well-known physics laws of ion separation and set dynamically the value of PDMT as a function of m/z. Namely, in our method, the PDMT is proportional to for FTICR, to for Orbitrap, to m/z for Q-TOF and is a constant for Quadrupole mass analyzer, respectively. The dynamic binning method was implemented in XCMS. Our further goal was to compare the performance of different lipidomics pre-processing tools to find differential compounds. We have generated set samples with 43 lipids internal standards differentially spiked to aliquots of one human plasma lipid sample using Orbitrap LC-MS/MS. The performance of the various pipelines using aligned parameter sets was quantified by a quality score system which reflects the ability of a pre-processing pipeline to detect differential peaks spiked at various concentration levels. The quality score indicates that the dynamic binning method improves the performance of XCMS (maximum p-value 9.8·10-3 of two-sample Wilcoxon test). The modified XCMS software was further compared with mzMine and Progenesis. The results showed that modified XCMS and Progenesis had a similarly good performance in the aspect of finding differential compounds. In addition, Progenesis shows lower variability as indicated by lower CVs, followed by XCMS and mzMine. The lower variability of Progenesis improve the quantification, however, provide an incorrect quantification abundance order of spiked-in internal standards. |
Institute | University of Groningen |
Last Name | Péter |
First Name | Horvatovich |
Address | Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands |
p.l.horvatovich@rug.nl | |
Phone | +31 (0)50 363 3341 |
Submit Date | 2020-09-25 |
Num Groups | 6 |
Total Subjects | 1 |
Study Comments | Different concentrations of lipid standard mixture were added to the plasma lipid extract aliquots |
Publications | Under review |
Raw Data Available | Yes |
Raw Data File Type(s) | mzML |
Analysis Type Detail | LC-MS |
Release Date | 2020-10-13 |
Release Version | 1 |
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Project:
Project ID: | PR001011 |
Project DOI: | doi: 10.21228/M8111X |
Project Title: | Dynamic binning |
Project Type: | MS analysis |
Project Summary: | Using dynamic binning theory to improve the peak detection in LC-MS based lipidomics |
Institute: | University of Groningen |
Department: | Department of Analytical Biochemistry |
Last Name: | Horvatovich |
First Name: | Péter |
Address: | Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands. |
Email: | p.l.horvatovich@rug.nl |
Phone: | +31 (0)50 363 3341 |
Funding Source: | China Scholarship Council grant No. 201708500094. This research was part of the Netherlands X-omics Initiative and partially funded by NWO, project 184.034.019. |
Publications: | Under review |