EVALUATION OF MS-DIAL AND MZMINE2 SOFTWARES FOR CLINICAL LIPIDOMICS ANALYSIS

Abstract

Lipidomics covers analysis of all lipid species in an organism. Lipid metabolism is one of the key factors to understand cellular processes at molecular level. Lipidomics has been used to find diagnostic and prognostic biomarkers in clinical sample (plasma, serum, urine, tissue). Today mass spectroscopy based approach dominates lipidomics and several computational platforms have been developed to process raw mass spectra data. However, there is no routine procedure for data processing in lipidomics. In present work, two different bioinformatics platforms, which are MS-DIAL and MZmine2, was compared for lipidomics analysis of plasma sample. Peak detection, identification and quantification parameters were investigated to understand advantages and disadvantages. In peak detection process, it was observed that MZmine2 detected more peak than MS-DIAL at same threshold level. In identification process, Lipidmaps database was used for identification. MZmine2 identifies more lipid than MS-DIAL. Semi-quantification is very important to find differentially expressed lipid species and biomarkers in clinical studies. MS-DIAL and MZmine2 calculated normalized peak intensities and results were compared to understand reproducibility. Average relative standard deviation of all peaks was calculated and results showed that MS-DIAL gives more reproducible results than MZmine2. In conclusion, MZmine2 and MS-DIAL could be used in clinical lipidomics studies.

Keywords

• Lipidomics,Bioinformatics,MS-Dial,MZmine2

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