This chapter focuses on the mass spectrometry data processing workflow. The first step consists of processing the raw MS data, leading to a feature matrix amenable for statistical analysis. The raw MS files contain the list of spectra acquired during the run, and each spectrum contains many pairs. In the field of metabolite fingerprinting, Direct Infusion Mass Spectrometry and Flow Injection Mass Spectrometry can be used to complement chromatography-based MS techniques. To reduce this complexity, several feature detection algorithms have been developed. A feature is characterized by a retention time, an m/z value and an intensity. In microarray data analysis it is relatively straightforward to compare the expression of some genes in one sample against the expression in a second one, because the RNA is hybridized to a particular “known” probe sequence. In case an accurate-mass spectrometer has been used, it is also important to determine the mass accuracy in the measurements.
|Title of host publication||Metabolomics|
|Subtitle of host publication||Practical Guide to Design and Analysis|
|Editors||Ron Wehrens, Reza Salek|
|Publication status||Published - 19 Aug 2019|