SpotClean

SpotClean adjusts for spot swapping in spatial transcriptomics data by estimating contamination rates and decontaminating bleed effects between nearby spots to improve the sensitivity and precision of downstream analyses.

Key Features:

• Contamination rate estimation: SpotClean estimates the contamination rate in observed spatial transcriptomics data affected by spot swapping.
• Decontamination of spot swapping effects: SpotClean removes spot swapping artifacts to provide more accurate estimates of gene-specific unique molecular identifier counts.
• Probabilistic modeling: SpotClean employs a probabilistic model to adjust for spot swapping in spatial transcriptomics experiments.

Scientific Applications:

• Marker gene analysis: SpotClean provides substantial improvements in marker gene analyses in spatial transcriptomics data.
• Clustering: SpotClean improves clustering performance, especially when tissue regions are not easily separated.
• Tumor versus normal tissue delineation: SpotClean improves tumor versus normal tissue delineation in cancer studies.
• Tumor burden estimation: SpotClean improves tumor burden estimation, increasing the potential for clinical and diagnostic applications of spatial transcriptomics technologies.

Methodology:

SpotClean uses a probabilistic model to estimate contamination rates and decontaminate spot swapping effects from observed unique molecular identifier counts in spatial transcriptomics data.