nanoTRON: a Picasso module for MLP-based classification of super-resolution data

MOTIVATION: Classification of images is an essential task in higher-level analysis of biological data. By bypassing the diffraction-limit of light, super-resolution microscopy opened up a new way to look at molecular details using light microscopy, producing large amounts of data with exquisite spatial detail. Statistical exploration of data usually needs initial classification, which is up to now often performed manually. RESULTS: We introduce nanoTRON, an interactive open-source tool, which allows super-resolution data classification based on image recognition. It extends the software package Picasso with the first deep learning tool with a graphic user interface. AVAILABILITY: nanoTRON is written in Python and freely available under the MIT license as a part of the software collection Picasso on GitHub (http://www.github.com/jungmannlab/picasso). All data files and code relevant for the review process of this paper can be accessed at https://datashare.biochem.mpg.de/s/iPBw9tj4OO9X4pC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.