We developed a machine-learning-aided analysis pipeline for highly multiplexed spatial transcriptomics and proteomics data from mouse brain tissue. The pipeline integrates image processing, 3D registration, cell/nucleus segmentation, RNA spot assignment, protein quantification, and downstream machine-learning analysis to investigate molecular organization at the sub-nuclear level.
The complete analysis pipeline is openly available on GitHub:
We’d be interested in feedback from the community.