Protocol for open-source Automated Universal high-content multiplex fluorescence for RNA in situ Analysis (AURA)

Abstract

In situ hybridization visualizes RNA in cells, but image analysis is complex. We present a protocol based on open-source software for automated high-content multiplex fluorescence in situ transcriptomics analysis. Steps include nuclei segmentation with a Fiji macro and quantification of up to 14 mRNA probes per image. We describe procedures for storing raw data, quality control images and the use of a Python app to summarize all the results in one spreadsheet detailing the number of single or co-positive cells.