title: A NEW METHOD OF PEAK DETECTION FOR ANALYSIS OF COMPREHENSIVE TWO-DIMENSIONAL GAS CHROMATOGRAPHY MASS SPECTROMETRY DATA.
abstract: We develop a novel peak detection algorithm for the analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) data using normal-exponential-Bernoulli (NEB) and mixture probability models. The algorithm first performs baseline correction and denoising simultaneously using the NEB model, which also defines peak regions. Peaks are then picked using a mixture of probability distribution to deal with the co-eluting peaks. Peak merging is further carried out based on the mass spectral similarities among the peaks within the same peak group. The algorithm is evaluated using experimental data to study the effect of different cut-offs of the conditional Bayes factors and the effect of different mixture models including Poisson, truncated Gaussian, Gaussian, Gamma, and exponentially modified Gaussian (EMG) distributions, and the optimal version is introduced using a trial-and-error approach. We then compare the new algorithm with two existing algorithms in terms of compound identification. Data analysis shows that the developed algorithm can detect the peaks with lower false discovery rates than the existing algorithms, and a less complicated peak picking model is a promising alternative to the more complicated and widely used EMG mixture models.
authors.affiliation: Biostatistics Core, Karmanos Cancer Insitute, Wayne State University, Detroit, MI 48201, USA.
authors.forename: Seongho
authors.initials: S
authors.lastname: Kim
authors.affiliation: Department of Computer Science, University of Massachusetts Boston Boston, MA 02125, USA.
authors.forename: Ming
authors.initials: M
authors.lastname: Ouyang
authors.affiliation: Department of Statistics, Chonnam National University, Gwangju 500757, Korea.
authors.forename: Jaesik
authors.initials: J
authors.lastname: Jeong
authors.affiliation: Department of Biostatistics, Indiana University, Indianapolis, IN 46202, USA.
authors.forename: Changyu
authors.initials: C
authors.lastname: Shen
authors.affiliation: Department of Chemistry, University of Louisville, Louisville, KY 40292, USA.
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhang
keywords: Bayes factor; GC×GC-TOF MS; metabolomics; mixture model; normal-exponential-Bernoulli (NEB) model; peak detection