Simple RGC: ImageJ plugins for counting retinal ganglion cells and determining the transduction efficiency of viral vectors in retinal wholemounts

TL;DR

Simple RGC provides a set of ImageJ plugins that streamline the counting and transduction efficiency analysis of retinal ganglion cells in retinal wholemount images, improving accuracy and reducing bias.

Contribution

The paper introduces three new ImageJ plugins specifically designed for efficient and unbiased analysis of retinal ganglion cells and viral transduction in retinal wholemounts.

Findings

Plugins enable quick and accurate RGC counting.

Plugins facilitate assessment of viral transduction efficiency.

Tools are freely available and easy to use.

Abstract

Simple RGC consists of a collection of ImageJ plugins to assist researchers investigating retinal ganglion cell (RGC) injury models in addition to helping assess the effectiveness of treatments. The first plugin named RGC Counter accurately calculates the total number of RGCs from retinal wholemount images. The second plugin named RGC Transduction measures the co-localisation between two channels making it possible to determine the transduction efficiencies of viral vectors and transgene expression levels. The third plugin named RGC Batch is a batch image processor to deliver fast analysis of large groups of microscope images. These ImageJ plugins make analysis of RGCs in retinal wholemounts easy, quick, consistent, and less prone to unconscious bias by the investigator. The plugins are freely available from the ImageJ update site https://sites.imagej.net/Sonjoonho/.