Efficient Algorithms for Liquid Chromatography Coupled Mass Spectrometry Based Protein Quantification
Report ID: TR-905-11Author: Khan, Zia
Date: 2011-08-00
Pages: 72
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Abstract:
Identification of genes and genetic pathways affected in disease and disease treatment is one of the driving aims of studies that conduct comprehensive, quantitative surveys of proteins across many experimental samples and replicates. The prevailing tool for conducting such surveys is a class of experimental techniques and instrumentation known as liquid chromatography coupled tandem mass spectrometry (LC-MS/MS). LC-MS/MS generates large data sets in the form of thousands to millions of mass spectra in a single experiment. Converting these spectra into interpretable quantitative measurements of proteins, their peptide fragments, or enrichment and depletion of their post-translational modifications presents a substantial computational challenge. This thesis describes a new application of space partitioning data structures and a series of algorithms that leverage the fast geometric queries supported by these data structures to significantly improve the speed and quality LC-MS/MS data analysis. In addition, this thesis develops a collection of methods, implemented in an open source software system called PVIEW (http://compbio.cs.princeton.edu/pview), that use the output of these algorithms to enable accurate quantification of proteins, protein fragments, and post-translational modifications. These methods are evaluated with respect to their quantitative accuracy and computational efficiency on a wide range of experimental data sets spanning several experimental methodologies and source protein samples.