Statistical Methods for Mass Spectrometry-based Imaging
Statistical methods are key for detecting signals (e.g., caused by an intervention or a disease) in presence of variation and uncertainty. This is particularly important for mass spectrometry-based imaging, where signals are obscured by variation between different biological replicates, the spatial variation within images of a same biological replicate, and the technical variation due to sample handling and spectral acquisition. Moreover, as spatial and mass resolution increase, the experiments become more prone to generating spurious associations, and to amplifying bias and confounding. This talk will discuss the importance of statistical inference when designing and analyzing mass spectrometry-based imaging experiments, as well as statistical methods and open-source software designed to facilitate the statistical inference tasks.
Presented at MSACL 2016 US