By Nick Eagles
We’ve recently been interested in exploring the (largely python-based) tools others have published to process spatial transcriptomics data for various end goals. A common goal is to integrate data from platforms like Visium, which provides some information about how gene expression is spatially organized, with other approaches with potentially better spatial resolution or gene throughput. In particular, we came across a paper by Biancalani, Scalia et al.
By Nick Eagles
As part of recent LIBD work with spatial gene expression, I recently was recommended the tool Space Ranger, which provides software pipelines walking Visium spatial RNA-seq samples through the steps we ultimately need to explore gene expression coupled with spatial information. In this blog post, I’ll explain how to start using Space Ranger at JHPCE, focusing heavily on the set-up details relevant to this cluster in particular.