About
TissUUmaps is a community-driven, open-source project. Everyone is welcome to contribute.
The SciLifeLab BioImage Informatics Unit (BIIF), part of SciLifeLab and NBIS, is a core contributor to the project.
History

TissUUmaps goes back to 2011. Carolina Wählby, then at the Broad Institute, was contacted by Mats Nilsson at Stockholm University, who had invented a method to sequence mRNA directly in tissue sections and needed computational tools to decode the image data. This led to a joint publication on in situ sequencing in Nature Methods in 2013, and a collaboration that is still ongoing.
In 2015, TissUUmaps became a research project of the Wählby lab at the Department of Information Technology, Uppsala University. The first paper describing the tool followed in 2020, and TissUUmaps 3, published in 2023, extended it from in situ sequencing to large-scale spatial omics data in general. Along the way, the project also produced new methods for pre- and post-processing of in situ sequencing data.
Over time, the SciLifeLab BioImage Informatics Unit (BIIF), originally founded by Carolina Wählby and now headed by Anna Klemm, took on a growing role in the project. In 2025, the BIIF began an architectural overhaul of the tool, which has since led to today's TissUUmaps 4.
Publications

Heliyon, doi: 10.1016/j.heliyon.2023.e15306, April 21. 2023.

Biological Imaging, doi: 10.1017/S2633903X23000053, February 20. 2023.

Bioinformatics, doi:10.1093/bioinformatics/btaa541, May 2020.
Funding
TissUUmaps is currently funded by:
- the SciLifeLab BioImage Informatics Unit (BIIF), through technology development projects (TDPs);
- the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), as a Research Data Community Project (RDCP).
Previously, it was funded by:
- the European Research Council, through an ERC consolidator grant to Carolina Wählby (ERC CoG 682810);
- the Swedish Foundation for Strategic Research (SSF), through the SysMic project (SB16-0046), with Staffan Strömblad as PI and Carolina Wählby as co-PI, and through the Big Data grant ‘Hierarchical Analysis of Temporal and Spatial Image Data - From intelligent data acquisition via smart data-management to confident predictions’, with Carolina Wählby as PI.


