Characterising phase variations in MALDI-TOF data and correcting them by peak alignment.


The use of MALDI-TOF mass spectrometry as a means of analyzing the proteome has been evaluated extensively in recent years. One of the limitations of this technique that has impeded the development of robust data analysis algorithms is the variability in the location of protein ion signals along the x-axis. We studied technical variations of MALDI-TOF measurements in the context of proteomics profiling. By acquiring a benchmark data set with five replicates, we estimated 76% to 85% of the total variance is due to phase variation. We devised a lobster plot, so named because of the resemblance to a lobster claw, to help detect the phase variation in replicates. We also investigated a peak alignment algorithm to remove the phase variation. This operation is analogous to the normalization step in microarray data analysis. Only after this critical step can features of biological interest be clearly revealed. With the help of principal component analysis, we demonstrated that after peak alignment, the differences among replicates are reduced. We compared this approach to peak alignment with a model-based calibration approach in which there was known information about peaks in common among all spectra. Finally, we examined the potential value at each point in an analysis pipeline of having a set of methods available that includes parametric, semiparametric and nonparametric methods; among such methods are those that benefit from the use of prior information.







Michael C. Fitzgerald

Professor of Chemistry

Dr. Fitzgerald’s research group is focused on studies of protein folding and function. The group utilizes a combination of covalent labeling strategies (e.g. protein amide H/D exchange and methionine oxidiation) and mass spectrometry techniques to investigate the thermodynamic properties of protein folding and ligand binding reactions. Current research efforts involve: (1) the development new biophysical methods that enable protein folding and stability measurements to be performed on the proteomic scale; and (2) the application of these new methods in the areas of disease detection, diagnosis, and therapy.


Edward F. Patz

James and Alice Chen Distinguished Professor of Radiology

There are numerous ongoing clinical studies primarily focused on the early detection of cancer.

The basic science investigations in our laboratory concentration on three fundamental translational areas,

1) Development of molecular imaging probes - We have used several different approaches to develop novel imaging probes that characterize and phenotype tumors.

2) Discovery of novel lung cancer biomarkers - We explored the use of proteomics, autoantibodies, and genomics to discover blood and tissue biomarkers for early cancer detection and phenotyping of cancer.

3) Host response to cancer - We study the native immune response to tumors as this may provide cues to relevant diagnostic and therapeutic targets. Most recently we have focused on intratumoral lymphocytes and their specific tumor antigens.


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