# LoQANT: An ImageJ Plugin for Quantifying Nuclear Staining in Immunohistochemistry and Immunofluorescence

## TL;DR

LoQANT is a new ImageJ plugin that helps scientists accurately measure nuclear staining in cells, improving reliability and efficiency over manual methods.

## Contribution

LoQANT introduces a single-cell-based, open-source tool for quantifying nuclear staining in immunohistochemistry and immunofluorescence.

## Key findings

- Manual scoring of nuclear staining leads to high variability and poor interobserver reliability.
- LoQANT provides reliable and efficient quantification of nuclear signals across different sample types.
- The plugin is freely available and supports both semiquantitative and quantitative measurements.

## Abstract

A large number of regulatory proteins are found in both the cytoplasm and the nucleus. Changes in their nuclear abundance are important for cellular signalling, biological activity, and disease mechanisms. Accurate quantification of nuclear staining is therefore essential in studies of cellular function, therapeutic targeting, drug design, and drug resistance. However, manual scoring is time-consuming, unsuitable for high-throughput applications, and introduces potential bias. As expected, manual scoring by six observers with varying levels of expertise led to highly variable results. Moreover, it was far from achieving good interobserver reliability. To overcome these limitations, LoQANT (Localisation and Quantification of Antigen Nuclear sTaining), an open, freely available ImageJ plugin, was developed for reliable and efficient quantification of nuclear signals. LoQANT is a single cell-based approach to assess the proportion of cells with a positive nuclear signal, independent of cytoplasmic staining, in both immunohistochemically and fluorescently stained samples across various sample types. It also provides semiquantitative and quantitative measurements of nuclear staining intensity. The script, its version for batch analysis, and complete user guide are available at GitHub.