SpatialQC: automated quality control for spatial transcriptome data.

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Although quality control (QC) critical for downstream data analyses, there is currently a lack of specialized tools for one-stop spatial transcriptome QC. Here, we introduce SpatialQC, a one-stop QC pipeline, which generates comprehensive QC reports and produces clean data in an interactive fashion. SpatialQC is widely applicable to spatial transcriptomic techniques.\nAVAILABILITY AND IMPLEMENTATION: source code and user manuals are available via https://github.com/mgy520/spatialQC, and deposited on Zenodo (https://doi.org/10.5281/zenodo.12634669).", "claims": [{"id": "claim-method", "statement": "Score comparisons are performed using SciPy's ttest_ind (Virtanen et al. 2020).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39051702", "locator": "sections[8] \"2.3 Platform compatibility\" paragraph 2", "quote": "Score comparisons are performed using SciPy's ttest_ind (Virtanen et al. 2020)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The stereo-seq data for Drosophila embryonic stages E14-E16h were obtained from StomicsDB, with the dataset identifier STDS0000060. 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