scGIST: gene panel design for spatial transcriptomics with prioritized gene sets
Mashrur Ahmed Yafi, Md. Hasibul Husain Hisham, Francisco Grisanti, James F. Martin, Atif Rahman, Md. Abul Hassan Samee
Abstract
A critical challenge of single-cell spatial transcriptomics (sc-ST) technologies is their panel size. Being based on fluorescence in situ hybridization, they are typically limited to panels of about a thousand genes. This constrains researchers to build panels from only the marker genes of different cell types and forgo other genes of interest, e.g., genes encoding ligand-receptor complexes or those in specific pathways. We propose scGIST, a constrained feature selection tool that designs sc-ST panels prioritizing user-specified genes without compromising cell type detection accuracy. We demonstrate scGIST's efficacy in diverse use cases, highlighting it as a valuable addition to sc-ST's algorithmic toolbox.