We are the Spatial Research lab – Welcome!

Our research focuses on developing innovative experimental methods as well as novel computational tools for spatially resolved omics in mammalian and plant tissue sections.

You can find out more about our team and our academic research activities under the Research section.

NEWS

JUNE 23-26TH 2020

THREE NEW PUBLICATIONS. The Swedish summer is here and June continues to deliver; we are happy to see three more articles from our group published between 23-26th of June. First out was a fantastic work on squamous cell carcinoma, a research project born from a collaboration between members of the Lundeberg group and Stanford University, and now published in Cell. It was followed by another collaborative project where deep learning was applied to breast tumour spatial transcriptomics data (Nature biomedical engineering). Lastly, the preprint “Molecular Atlas Of The Adult Mouse Brain” has now made its way to be a peer-reviewed publication in Science advances. We are thankful to all the involved people making these publications possible and look forward to more great research being published in the future!

all articles

JUNE 5TH 2020

CONGRATULATIONS DR. BERGLUND! 🎓 Emelie Berglund successfully defended her thesis with the title “Molecular and Spatial Profiling of Prostate Tumors” on June 5th. We are all proud of her great achievement and wish her all the best in her future endeavours!

Her thesis can be read online here and a list of the publications she has authored can be found here.

to thesis

MAY 4TH 2020

NEW REVIEW OUT. “Spatially Resolved Transcriptomes—Next Generation Tools for Tissue Exploration” is new review article written by our own Michaela, Joseph, and Joakim! In this publication you can read about the different spatially resolved transcriptomics technologies available as of today, how they compare against each other, and what we may expect from the future.

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APR 29TH 2020

SPATIALCPIE FOR ST ANALYSIS. “SpatialCPie” is a new R/Bioconductor package, developed by Joseph and Ludvig Bergenstråhle, which can be used for visualization of clusters at multiple resolutions and proportions for your spatial transcriptomics data. Read more about the tool on GitHub, Bioconductor, or the BMC Genomics publication “SpatialCPie: an R/Bioconductor package for spatial transcriptomics cluster evaluation”.

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