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Tangram is a Python package, written in PyTorch and based on scanpy , for mapping single-cell (or single-nucleus) gene expression data onto spatial gene expression data. The single-cell dataset and the spatial dataset should be collected from the same anatomical region/tissue type, ideally from a biological replicate, and need to share a set of genes. Tangram aligns the single-cell data in space by fitting gene expression on the shared genes. The best way to familiarize yourself with Tangram is to check out our tutorials.


Tangram News

  • On Jan 28th 2021, Sten Linnarsson gave a talk at the WWNDev Forum and demostrated their mappings of the developmental mouse brain using Tangram.

  • On Mar 9th 2021, Nicholas Eagles wrote a blog post about applying Tangram on Visium data.

  • The Tangram method has been used by our colleagues at Harvard and Broad Institute, to map cell types for the developmental mouse brain -see Fig. 2 [`Nature(2021)<>`_]

  • Tangram is now officially a part of Squidpy

Citing Tangram

Tangram has been released in the following publication

Biancalani* T., Scalia* G. et al. - _Deep learning and alignment of spatially-resolved whole transcriptomes of single cells in the mouse brain with Tangram biorXiv 10.1101/2020.08.29.272831 (2020)

Release Notes

1.0.0 2021-08-06 - Initial Release