Gelato streamlines reproducible and auditable assembly of Western blot figures
Gelato is a free Fiji/ImageJ plugin that streamlines the creation of reproducible and auditable Western blot figures by logging processing coordinates and enabling reconstruction from raw images, thereby enhancing scientific rigor and reducing the burden on researchers and reviewers.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer
For decades, scientists have relied on a technique called Western blotting to see if specific proteins are present in a sample. It is a fundamental tool in biology, used to confirm that a cell is making a certain molecule or to measure how much of it exists. The process leaves behind a visual record: a dark band on a piece of membrane where the protein has been detected. To make sense of these bands, researchers place them next to a ruler-like standard that shows the size of different molecules. However, turning these raw images into a final picture for a scientific paper has long been a messy, manual task. Scientists must take separate photos of the size standard and the protein bands, then use graphic design software to cut, rotate, and paste them together. This process is prone to human error, and once the pieces are pasted, the original connection between the final image and the raw data is often lost. This makes it difficult for other scientists to check the work or verify that the final picture accurately represents the original experiment.
A team of researchers at Tel Aviv University has developed a solution to this problem called Gelato. This is a free software tool that runs inside a popular image program used by scientists. Instead of manually cutting and pasting images, Gelato guides the user through a single, streamlined process. The researcher uploads the original photos of the size standard and the protein bands. The software then allows the user to click on the size markers to record their values and click on the protein bands to select the areas they want to include. As the user works, the software quietly records every single move: exactly which part of the image was chosen, how it was rotated, and how it was resized. When the final figure is assembled, the software exports the image along with a detailed log file that contains the complete history of how that image was built.
The value of this approach lies in its ability to create a perfect, auditable trail. When a scientist submits a paper using Gelato, they can also submit the log file. A reviewer can then load this file into the software, which automatically pulls up the original raw images and reconstructs the final figure exactly as it was made. The reviewer can see the original bands and the size markers side-by-side with the final published image, with every cut and rotation clearly highlighted. This removes the guesswork and the need to trust that the author did not accidentally or intentionally misrepresent the data. The researchers note that in a review of hundreds of recent papers, the vast majority of published figures lacked the raw source images or clear indications of the size markers, making verification nearly impossible. While some errors in figure assembly are simply accidental, the lack of transparency makes it hard to distinguish between a mistake and misconduct.
Gelato does not replace the scientist's judgment or responsibility for their data. Instead, it provides a practical way to ensure that the journey from the raw experiment to the published picture is clear and open to inspection. By making the assembly process automatic and the record-keeping invisible to the user, the tool reduces the burden on researchers while strengthening the integrity of the science. The software is open for anyone to use, and the researchers have made the code available for others to examine and improve. This work addresses a long-standing need in the scientific community to preserve the link between the final image and the original data, ensuring that the visual evidence supporting scientific discoveries remains trustworthy and easy to verify.
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