In the analysis of spatial transcriptomic experiments, the recently proposed SpaRTaCo model (Sottosanti & Risso, 2022) allows for the simultaneous clustering of genes and cells of a tissue sample, providing interesting insights abuove the underlying biological processes. In this work, we discuss how to integrate external knowledge such as manual cell-type annotations to inform gene clustering, with the by-product of substantially reducing the computational burden.
Clustering genes spatial expression profiles with the aid of external biological knowledge
Andrea Sottosanti
;Stefania Pirrotta;Enrica Calura;Davide Risso
2023
Abstract
In the analysis of spatial transcriptomic experiments, the recently proposed SpaRTaCo model (Sottosanti & Risso, 2022) allows for the simultaneous clustering of genes and cells of a tissue sample, providing interesting insights abuove the underlying biological processes. In this work, we discuss how to integrate external knowledge such as manual cell-type annotations to inform gene clustering, with the by-product of substantially reducing the computational burden.
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