image: On the left: single-cell analysis of bone marrow samples from patients with myelodysplastic syndromes. On the right: spatial analysis of a murine brain section. In both cases, each point represents a cell, colored according to the cell type identified by Cell Marker Accordion.
Credit: University of Trento
"With Cell Marker Accordion we wanted to build a tool that helps researchers not only to classify cells, but also to understand why they have been classified in a certain way", explains Emma Busarello, a PhD candidate in Biomolecular sciences at the University of Trento and first author of the work. "Often software give a result, but do not say how they got there. We wanted to do something more transparent and useful for people working in clinical settings."
The name of the instrument – "Accordion" – recalls the idea of harmonizing different data to provide a more robust result.
The software has been designed to help identify cell types in biological samples both under normal conditions and in the presence of disease. It can, for example, indicate the presence of leukemic stem cells or tumour plasma cells, also suggesting which genes could be involved in the alterations.
"Our tool does not limit itself to indicating what type of cell is present, but also helps to find out which genes make that cell unique and different from the others," adds Toma Tebaldi, professor at the Department of Cellular, Computational and Integrative Biology - Cibio of the University of Trento and corresponding author of the research. "This can help identify new biomarkers or therapeutic targets."
One of its strengths is accessibility. In addition to the software package for those with bioinformatics skills, the Accordion has a web version with an intuitive interface that can easily be used even by non-programmers.
The project was developed at the Cibio Department and involved research groups with specific expertise, from brain tumours to blood tumours. Among the partners are the teams coordinated by Paolo Macchi, Maria Caterina Mione, Luca Tiberi of the University of Trento and Gabriella Viero of CNR. They worked with Giulia Biancon (Policlinico di Milano), the University of Trondheim and Stephanie Halene of the Yale School of Medicine. The study was supported by Airc, Ail Trento and Bolzano, Fondazione Vrt, a cascade call of the National Center for the Development of Gene Therapy and RNA-based drugs (NRRP) and the Cibio excellence department.
One of the future goals of the project is to adapt the instrument to new types of data and keep it updated over time, to make sure that the scientific community can always count on a reliable tool. "A scientific software does not end with a publication," concludes Tebaldi. "quite the contrary: it must be maintained, constantly improved, made more and more useful in line with new discoveries. This too is a service to research."
About the article
The article "Cell Marker Accordion: interpretable single-cell and spatial omics annotation in health and disease" was published in Nature Communications and can be found at: https://doi.org/10.1038/s41467-025-60900-4
Journal
Nature Communications
Subject of Research
Cells
Article Title
Cell Marker Accordion: interpretable single-cell and spatial omics annotation in health and disease
Article Publication Date
7-Jul-2025