MICCRA – a pipeline for the analysis of imaging mass cytometry data
We have developed MICCRA (Modular IMC Cell Characterization with automatic Region Assembly), a pipeline for modular processing of IMC data from raw files into expression-characterized single cells requiring minimal user input. We applied MICCRA to analyze multiple samples from 25 uveal melanoma (UM) patients obtained in the framework of the Treat 20 Plus project. Here, we show that the pipeline consistently identifies the core tumor region as well as the margin, segmenting the image into annotated cell types. We will also report the comparative performance of the pipeilne with other approaches.
Anika Rettig has finished her masters in bioinformatics in spring 2019 and has since worked as a bioinformatician in the group of Marie-Laure Yaspo at Max Planck Institute Berlin. Both her master’s thesis and her following work have been focused on image processing, using traditional computer vision techniques as well as machine learning strategies.
Max-Planck-Institut für molekulare Genetik Berlin, AG Yaspo