Benchmark pitfalls expose need for expert-guided spatial clustering
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TL;DR - Benchmarking spatial transcriptomics clustering tools is undermined by reproducibility, data, and evaluation limitations. Combining computational consensus with expert histology and cell-biology feedback can produce evaluations more faithful to multiscale biology and accelerate discovery.
- Spatial clustering benchmarks often lack reproducibility and suitable data.
- Existing evaluation strategies may not capture biology across spatial scales.
- Computational consensus alone is insufficient to overcome these limitations.
- Domain-expert feedback provides biological context for more reliable assessment.
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Benchmark pitfalls expose need for expert-guided spatial clustering
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TL;DR - Benchmarking spatial transcriptomics clustering tools is undermined by reproducibility, data, and evaluation limitations. Combining computational consensus with expert histology and cell-biology feedback can produce evaluations more faithful to multiscale biology and accelerate discovery.
- Spatial clustering benchmarks often lack reproducibility and suitable data.
- Existing evaluation strategies may not capture biology across spatial scales.
- Computational consensus alone is insufficient to overcome these limitations.
- Domain-expert feedback provides biological context for more reliable assessment.