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.

Submitted: December 8, 2005 · Accepted: April 17, 2006 · Published: April 21, 2006

Recommended Citation

Birkner, Merrill D.; Hubbard, Alan E.; van der Laan, Mark J.; Skibola, Christine F.; Hegedus, Christine M.; and Smith, Martyn T. (2006) "Issues of Processing and Multiple Testing of SELDI-TOF MS Proteomic Data," Statistical Applications in Genetics and Molecular Biology: Vol. 5 : Iss. 1, Article 11.
DOI: 10.2202/1544-6115.1198
Available at: http://www.bepress.com/sagmb/vol5/iss1/art11