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Gene panel selection for targeted spatial transcriptomics
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DOI：10.1186/s13059-024-03174-1.png)
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Abstract
En 中文
Targeted spatial transcriptomics hold particular promise in analyzing complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is their reliance on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method performing gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.
Keywords:
Gene panel selection
Targeted spatial transcriptomics
Single-cell RNA sequencing
Platform effect
Cell type hierarchy
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