Location: MIC-Arena, Maria-Goeppert-Str 1a, 23562 Lübeck
Title: SCiLS Lab: software for analysis and interpretation of large MALDI-IMS datasets
Abstract: Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI Imaging) is an innovative and powerful measurement technique of analytical chemistry which, given a thin sample, is able to reveal its spatial chemical composition in the wide molecular range. MALDI Imaging produces an image, where for each pixel a high-dimensional mass spectrum is measured. Analysis and interpretation of this huge amount of data is a mathematical, statistical and computational challenge.
In this talk we present computational methods for automated analysis of large MALDI Imaging datasets. They are implemented in our software SCiLS Lab for visualization and analysis of large MALDI Imaging data, in particular for 3D MALDI Imaging datasets. For unsupervised data mining, we propose using the spatial segmentation approach. In order to reduce significant spectrum-to-spectrum variation, we propose to use edge-preserving image denoising prior to segmentation. For segmentation, we developed a new efficient clustering method, called as bisecting k-means, which is suitable for hierarchical clustering of a large MALDI Imaging dataset. After achieved a reasonable segmentation map, the software automatically browse through all m/z images and finds statistically relevant m/z-values for every cluster.
