SpatialArtifacts

SpatialArtifacts provides a data-driven two-step workflow to identify, classify, and handle spatial artifacts in spatial transcriptomics data.

Key Features:

• MAD-based outlier detection: The package uses median absolute deviation-based outlier detection as the first step of its workflow.
• Morphological image processing: The package applies fill, outline, and star pattern morphological operations to detect edge and interior artifacts.
• Multi-platform support: The package supports 10x Genomics Visium (standard and HD) for consistent quality control across different spatial resolutions.
• Artifact classification: The workflow classifies detected artifacts into distinct categories including edge and interior artifacts.

Scientific Applications:

• Spatial transcriptomics quality control: The package enables consistent quality control across different spatial resolutions in spatial transcriptomics experiments.
• Artifact handling in Visium data: The package identifies and classifies spatial artifacts in both standard and HD 10x Genomics Visium data.

Methodology:

The workflow combines median absolute deviation (MAD)-based outlier detection with morphological image processing using fill, outline, and star patterns to detect edge and interior artifacts.