top of page

Spatial Proteomics of the Spleen




The spleen, a vital organ in the immune system, has been the subject of extensive research due to its multifaceted roles in immune response, blood filtration, and the recycling of iron from aged red blood cells. Despite significant progress in understanding the spleen's cellular and molecular constituents, comprehensive knowledge of its complex biology, especially at the protein level, remains elusive.

While recent advances in spatial transcriptomics data is generating unprecedented wealth of data that shed light on the spatial organization and functional relationships of genes, such understanding at the proteomic level remain elusive. Here we will analyze newly-developed spatial proteomics data from our collaborators to unravel the intricate biology of the spleen generated by our collaborators, thereby advancing our understanding of its diverse roles in immunity and disease.

To fully harness the potential of spatial proteomics, we will adopt and develop computational toolsets used to analyze spatial transcriptomic datasets, ex. Giotto, Spateo, and/or stLearn. Through the integration of spatial proteomics data with other omics datasets, we aim to generate a comprehensive and cohesive understanding of the spleen's biology at multiple levels of cellular organization.


Data Integration, Data viz, scRNA-Seq, Image Processing

Project Stage


Avg. Hours / Week


Project Provider

Kuan-Lin Huang, PhD

Commitment (Months)


Spots Open


Project Lead

Matías Aiskovich

Publication if successful?


Trainee authorship criteria (if applicable)

Generate meaningful codes/results that go into final version of the manuscript

Single-Cell RNA-Seq assessment should be performed in Python using scanpy. Preference will be given to trainees who complete the Spateo tutorials: or the stLearn tutorials:

Required Skill Assessments

Single-Cell RNA-Seq

Python for Data Science

Python Programming

bottom of page