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 abouve 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.