This book presents an overview of computational and statistical design
and analysis of mass spectrometry-based proteomics, metabolomics, and
lipidomics data. This contributed volume provides an introduction to the
special aspects of statistical design and analysis with mass
spectrometry data for the new omic sciences. The text discusses common
aspects of design and analysis between and across all (or most) forms of
mass spectrometry, while also providing special examples of application
with the most common forms of mass spectrometry. Also covered are
applications of computational mass spectrometry not only in clinical
study but also in the interpretation of omics data in plant biology
studies.
Omics research fields are expected to revolutionize biomolecular
research by the ability to simultaneously profile many compounds within
either patient blood, urine, tissue, or other biological samples. Mass
spectrometry is one of the key analytical techniques used in these new
omic sciences. Liquid chromatography mass spectrometry, time-of-flight
data, and Fourier transform mass spectrometry are but a selection of the
measurement platforms available to the modern analyst. Thus in practical
proteomics or metabolomics, researchers will not only be confronted with
new high dimensional data types--as opposed to the familiar data
structures in more classical genomics--but also with great variation
between distinct types of mass spectral measurements derived from
different platforms, which may complicate analyses, comparison, and
interpretation of results.
