Observed arrival · 2026-11-08
stRSC: scoring spatial gene-expression predictions
A browser tool and Python toolkit for evaluating gene-expression predictions made from stained tissue images.
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- Spatial transcriptomics method developers and evaluators
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- Scale decomposition supports Fourier grids, spot-neighbor graphs, and single-cell graphs.
Field notes
The calculation begins with raw counts: each RNA molecule is assigned at random to one of two halves, and the prediction and halves are decomposed across spatial scales. For the decomposition, the site describes Fourier bases on regular grids, neighbor graphs for spots, and cell graphs for single-cell data. It averages scores over repeated splits and links its paper figures and data from the results section.
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