SPARKLE: evidence-constrained correction of local RNA leakage in high-resolution spatial transcriptomics
- 1BGI-Shenzhen
Abstract
High-resolution sequencing-based spatial transcriptomics, including Stereo-seq and Visium HD, aggregates dense capture units into cell-resolved expression matrices. During tissue processing and permeabilization, RNA released from source cells can spread to neighbouring capture locations, reducing cell-type specificity and biasing downstream analyses. Here we developed SPARKLE (Spatial Ambient RNA Kernel-based Leakage Estimator), a cell-level correction method that uses capture locations outside cell-segmentation masks as within-sample spatial evidence of leakage. SPARKLE fits sparse spatial kernels to out-of-mask observations to estimate a sample-level propagation scale and gene-specific leakage coefficients. It corrects only genes supported by out-of-mask goodness of fit and uses expression-dependent conservative shrinkage to protect highly expressing source cells. In ten simulated scenarios, SPARKLE achieved the highest cell-wise concordance in eight and the lowest RMSE in nine. In axolotl brain, mouse brain and human ovarian cancer, SPARKLE removed ectopic marker signal from neighbouring cells while retaining source-cell expression, improved agreement with independent single-cell and single-nucleus references, and recovered an inferred fibroblast-to-tumor COL1A2-SDC4 communication route that was obscured by ectopic COL1A2 expression. Conclusions remained stable across plausible spatial scales and background-bin sizes. Runtime scaled near-linearly with tissue-window area and was further accelerated on GPU. SPARKLE is therefore a reference-free, fast and scalable method for correcting local RNA leakage from evidence contained within each sample, improving the reliability of cell-type localization, tissue-compartment identification and cell-cell communication inference.
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BibTeX
@misc{wang2026sparkle,
title = {{SPARKLE: evidence-constrained correction of local RNA leakage in high-resolution spatial transcriptomics}},
author = {S. Wang and B. Zhu and S. Li and X. Wei},
howpublished = {bioRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.12.744394},
url = {https://www.biorxiv.org/content/10.64898/2026.08.12.744394v2},
note = {CC BY},
}
RIS
TY - UNPB
TI - SPARKLE: evidence-constrained correction of local RNA leakage in high-resolution spatial transcriptomics
AU - S. Wang
AU - B. Zhu
AU - S. Li
AU - X. Wei
PY - 2026
DA - 2026/08/12
PB - bioRxiv
DO - 10.64898/2026.08.12.744394
UR - https://www.biorxiv.org/content/10.64898/2026.08.12.744394v2
AB - High-resolution sequencing-based spatial transcriptomics, including Stereo-seq and Visium HD, aggregates dense capture units into cell-resolved expression matrices. During tissue processing and permeabilization, RNA released from source cells can spread to neighbouring capture locations, reducing cell-type specificity and biasing downstream analyses. Here we developed SPARKLE (Spatial Ambient RNA Kernel-based Leakage Estimator), a cell-level correction method that uses capture locations outside cell-segmentation masks as within-sample spatial evidence of leakage. SPARKLE fits sparse spatial kernels to out-of-mask observations to estimate a sample-level propagation scale and gene-specific leakage coefficients. It corrects only genes supported by out-of-mask goodness of fit and uses expression-dependent conservative shrinkage to protect highly expressing source cells. In ten simulated scenarios, SPARKLE achieved the highest cell-wise concordance in eight and the lowest RMSE in nine. In axolotl brain, mouse brain and human ovarian cancer, SPARKLE removed ectopic marker signal from neighbouring cells while retaining source-cell expression, improved agreement with independent single-cell and single-nucleus references, and recovered an inferred fibroblast-to-tumor COL1A2-SDC4 communication route that was obscured by ectopic COL1A2 expression. Conclusions remained stable across plausible spatial scales and background-bin sizes. Runtime scaled near-linearly with tissue-window area and was further accelerated on GPU. SPARKLE is therefore a reference-free, fast and scalable method for correcting local RNA leakage from evidence contained within each sample, improving the reliability of cell-type localization, tissue-compartment identification and cell-cell communication inference.
ER -