tools are inappropriate because of the problems of multiple testing and multiple co-variants. To address this there is increasing interest in the use of multivariate statistics and machine learning approaches to process the datasets obtained. In this chapter we will examine why multivariate statistical tools are often more appropriate than their univariate counterparts, and introduce some common unsupervised and supervised approaches used in lipidomics, including principal components analysis, hierarchical cluster analysis, partial least squares discriminate analysis and machine learning approaches such as random forests. The application of multivariate statistics will then be demonstrated in applications that produce one-dimensional (direct infusion mass spectrometry), two-dimensional (liquid chromatography mass spectrometry) and three-dimensional (mass spectrometry imaging, liquid chromatography ion mobility mass spectrometry) datasets as part of their lipidomic workflows. Chapter 3. Low-flow Rate Separations of Lipids. Hanne Roberg-Larsen and Steven Ray Wilson. Pages 49 - 73 Low-flow rate separation systems (e.g. nano liquid chromatography and capillary electrophoresis) can allow for enhanced sensitivity and/or resolution. Such systems can be used for detecting low-abundant lipids, performing lipidomics of very small amounts of sample, and for studying interactions between lipids and other compounds, e.g. drugs. Low-flow separation systems are highly compatible with mass spectrometry, on-line sample preparation, and multi-dimensional chromatography, for example. Chapter 4. Ion Mobility - Mass Spectrometry for Lipid Analysis. Giuseppe Paglia and Giuseppe Astarita. Pages 74 - 87 Ion mobility (IM) is a post ionization tool that can be used to separate lipid ions in the gas phase according to their charge, shape and size. IM can be combined with mass spectrometry (MS), adding three main benefits to traditional approaches for lipid analysis. First, IM allows determination of the collision cross section of a lipid molecule, a physicochemical property related to the conformational structure, which facilitates lipid identification. Second, IM improves the peak capacity and the signal-to-noise ratio, allowing the separation of interfering isobaric lipid species. Third, IM allows a new set of hybrid fragmentation experiments that combine collision-induced dissociation with gas phase separation, improving the specificity of the tandem MS-based approaches. Here, we review the current applications of IM-MS for lipid analysis. Chapter 5. Mass Spectrometry Imaging of Lipids. Shazia Khan and Ruth Andrew. Pages 88 - 121 Mass Spectrometry Imaging (MSI) has evolved as an exciting technology that can be used to map lipids on tissue surfaces, with many research, industrial and clinical applications. A wide variety of lipids can be spatially localised in both positive and negative modes (e.g. highlighted in cancer, skin and brain) and ionisation approaches such as Matrix-Assisted Laser Desorption/Ionisation (MALDI), Secondary Ion Mass Spectrometry (SIMS) and Desorption Electrospray Ionisation (DESI) bring different strengths and weaknesses, including mass ranges and resolution, fragmentation profiles and spatial resolution. This chapter explores the technical differences of the ionisation types applied to lipid MSI, and offers insight into appropriate choices for spatially profiling specific lipid classes. Novel approaches to enhance ionisation through derivatisation, matrix chemistry and nanomaterials offer the potential to reveal a greater proportion of the lipidome. MSI offers opportunities to profile lipid classes, but in the absence of chromatography cannot yet confidently assign stereochemistry, a weakness that may be addressed using ion mobility. Advances in integrating ion mobility and improvements in handling the large datasets generated, in combination with current methodologies, offer exciting future opportunities to decipher the complex lipid patterns in health and disease. Chapter 6. Derivatisation for Direct Infusion - and Liquid Chromatography - Mass Spectrometry. Y. Wang and W. J. Griffiths. Pages 122 - 147 The concept of derivatisation to enhance the ion signal is almost as old as biological mass spectrometry (MS) itself. In this chapter we will concentrate our attention on derivatisation methods to enhance ion signals in desorption ionisation methods, primarily matrix-assisted laser desorption/ionisation (MALDI) and electrospray ionisation (ESI), both for direct-infusion (DI)-MS and liquid chromatography (LC)-MS. Derivatisation provides advantages in lipidomics, as besides enhancing ion current can add specificity in terms of both solution chemistry and gas-phase ion chemistry via the collision-induced dissociation (CID) process. There are downsides to derivatisation methods, namely in terms of added complexity and time in sample preparation and