A benchmarking for computational methods of Mass spectrometry based lipidomics data analysis

Lipids are a large group of biomolecules involved in biological processes such as energy homeostasis, formation of cellular membranes and cell signaling [1, 2]. The total lipid content in a cell is called lipidome and lipidomics is the study of lipidomes using the prin ciples and techniques of analytical chemistry [3]. The main techniques for the analysis of lipids are based on mass spectrometry [4].The structural diversity and complexity of lipids, however, also requires the development and application of new algorithms and software tools that are specifically directed at processing data from lipid analyses [5]. Lipid databases like LIPIDMAPS [6] and Lipid Data Analyzer [7] are specialized that significantly aid lipidomics researches in compound and pathway annotation. There are also LIPIDMAPS presents an example of such a general lipid database that provides critical chemical information necessary for compound annotation. In this research, a number of lipidomics algorithms and softwares based on mass spectrometry were compared. We have presented a benchmark about open source software which were developed and used for lipidomics analysis include Lipid Profiler [8], LipidInspector [9], LipidQA [10], LIMSA [11], Fatty Acid Analysis Tool (FAAT) [12] and Analysis of Lipid Experiments (ALEX) [13]

Keywords:

Algorithms , Mass spectrometry , Lipidomics , Softwares , Databases