Free to use, CellForgeR enables researchers to explore gene expression data without programming skills; Helder Nakaya helped improve the platform’s interface and features
An online tool developed by Brazilian researchers aims to simplify the analysis of genetic data from individual cells, an approach that enables more detailed investigations into tissue composition and the mechanisms involved in disease. Available free of charge, CellForgeR can be used by scientists with no programming experience.
The platform was developed by researchers from the University of Campinas (Unicamp), São Paulo State University (Unesp), and the University of São Paulo (USP). Contributors include Helder Nakaya, head of the Integrative Biology research group at the Institut Pasteur de São Paulo (IPSP) and a professor at USP’s School of Pharmaceutical Sciences, who helped improve the tool’s interface, usability, and features.
The platform was designed to analyze data generated through single-cell RNA sequencing, a technique known as single-cell RNA-seq. While analyses of tissue samples can provide an average picture of gene expression, this approach allows researchers to identify which genes are active in each cell analyzed.
This level of resolution helps reveal differences between cells that, despite being part of the same tissue or belonging to the same category, may have distinct characteristics and functions. In a tumor, for example, the technique enables researchers to investigate different cell populations and the expression of genes of interest in each of them.
Analyzing these data, however, typically requires bioinformatics expertise and the computational capacity to process large volumes of information. CellForgeR seeks to lower these barriers through an interface that allows researchers to select parameters, cell types, and genes of interest using menus and buttons.
From prototype to the scientific community
Nakaya’s contribution to the project focused on the challenge of turning a tool that worked in the laboratory into a platform that could be used by the broader scientific community. To achieve this, he discussed aspects such as interface layout, ease of use, available features, and the processing capacity required for analyses with the team.
“Building a prototype that works well in the laboratory is one thing; releasing it to the community is another,” he says. “When developing software, it is not enough to create a tool that performs the analysis well. You also need to think about ease of use, design, and features.”
The researcher emphasizes that these decisions affect both the platform’s presentation and the feasibility of the analyses. His contributions included suggestions about which features could be useful to users and which operations might place excessive demands on the server’s processing capacity.
CellForgeR runs on the Scientific Computing Cluster at Unicamp’s Institute of Biology and is accessed through a web browser, with no installation required on the user’s computer. The platform supports both researchers’ own data and publicly available datasets.
More possibilities for research
By making analysis more accessible, the tool can help scientists across different fields explore existing data and formulate new research questions. A researcher interested in cancer, for example, can investigate the expression of a gene in immune cells within a tumor and compare it with its expression in other cell types.
CellForgeR was developed with the participation of Diogo de Moraes, from Unesp, and Marcelo Mori, a professor at Unicamp’s Institute of Biology, alongside collaborators from the three universities. The teams also plan to offer training for researchers interested in analyzing single-cell RNA sequencing data.
The platform is available at labeapps.ib.unicamp.br/CellForgeR. To request an account or contact the team, interested researchers can email diogo.moraes@unesp.br.
With information from Agência FAPESP