MOTIVATION: Microsatellite instability (MSI) is a molecular marker of DNA mismatch repair deficiency frequently at play in oncogenesis. MSI testing is used for diagnostic, prognostic and therapeutic purposes in several cancers. The current gold standard analysis for microsatellite status is based on length distribution analysis of multiplex-PCR generated DNA fragments from tumor samples which is a laborious and time consuming method. Next generation sequencing (NGS) using amplicon panels is an easy, accurate and scalable technique to determine both the microsatellite status and tumor genome mutations at the same time. Here, we describe MIAmS, an application designed to tag microsatellite status from amplicon NGS of tumor samples. Interestingly, this tool does not require paired normal tissue for comparison. In addition, this scalable application provides a user-friendly report for the interpretation of the results by biologists and exhibits a strong accuracy and robustness for determination of the MSI status. AVAILABILITY: https://github.com/bialimed/miams. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online, evaluation data are available at http://www.ebi.ac.uk/ena/data/view/PRJEB31725.

In biology and pathology, immunofluorescence microscopy approaches are leading techniques for deciphering molecular mechanisms of cell activation and disease progression. Although several solutions for image analysis exist, totally nonsubjective image analysis remains difficult. There is therefore a strong need for analysis procedures highly reproducible, avoiding thresholds and selection of objects of interest by hand. To address this need, we describe a fully automatic segmentation of cell nuclei in 2-D immunofluorescence images. The method merges segments of the image to fit with a nuclei model learned by a trained Random Forest classifier. The merging procedure explores efficiently the fusion configurations space of an over-segmented image by using minimum spanning tree of its region adjacency graph.