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Title: Issues of processing and multiple testing of SELDI-TOF MS proteomic data.

Authors: Birkner, Merrill D; Hubbard, Alan E; van der Laan, Mark J; Skibola, Christine F; Hegedus, Christine M; Smith, Martyn T

Published In Stat Appl Genet Mol Biol, (2006)

Abstract: A new data filtering method for SELDI-TOF MS proteomic spectra data is described. We examined technical repeats (2 per subject) of intensity versus m/z (mass/charge) of bone marrow cell lysate for two groups of childhood leukemia patients: acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). As others have noted, the type of data processing as well as experimental variability can have a disproportionate impact on the list of "interesting'' proteins (see Baggerly et al. (2004)). We propose a list of processing and multiple testing techniques to correct for 1) background drift; 2) filtering using smooth regression and cross-validated bandwidth selection; 3) peak finding; and 4) methods to correct for multiple testing (van der Laan et al. (2005)). The result is a list of proteins (indexed by m/z) where average expression is significantly different among disease (or treatment, etc.) groups. The procedures are intended to provide a sensible and statistically driven algorithm, which we argue provides a list of proteins that have a significant difference in expression. Given no sources of unmeasured bias (such as confounding of experimental conditions with disease status), proteins found to be statistically significant using this technique have a low probability of being false positives.

PubMed ID: 16646865 Exiting the NIEHS site

MeSH Terms: Acute Disease; Algorithms; Bone Marrow Cells/metabolism; Child; Data Interpretation, Statistical; Humans; Leukemia, Myeloid/metabolism*; Neoplasm Proteins/metabolism*; Precursor Cell Lymphoblastic Leukemia-Lymphoma/metabolism*; Probability; Proteomics/methods*; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods*

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