Exploring science is typically characterized by a lot of puzzles, frustrations or even failures. This weblog is mainly intended to record my working, thinking and knowledge acquisitions. I expect that some reflection would refresh my mind from time to time, and motivate me to move further, and hopefully give me a better view about even changing the landscape of bioinformatics.
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Thursday, April 7, 2011
SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists
Motivation: Alignment of multiple liquid chromatography/mass spectrometry (LC/MS) experiments is a necessity today, which arises from the need for biological and technical repeats. Due to limits in sampling frequency and poor reproducibility of retention times, current LC systems suffer from missing observations and non-linear distortions of the retention times across runs. Existing approaches for peak correspondence estimation focus almost exclusively on solving the pairwise alignment problem, yielding straightforward but suboptimal results formultiple alignment problems.
Results: We propose SIMA, a novel automated procedure for alignment of peak lists from multiple LC/MS runs. SIMA combines hierarchical pairwise correspondence estimation withsimultaneous alignment and global retention time correction. It employs a tailored multidimensional kernel function and a procedure based on maximum likelihood estimation to find the retention time distortion function that best fits the observed data. SIMA does not require a dedicated reference spectrum, is robust with regard to outliers, needs only two intuitive parameters and naturally incorporates incomplete correspondence information. In a comparison with seven alternative methods on four different datasets, we show that SIMA yields competitive and superior performance on real-world data.