jazzPanda

jazzPanda finds spatially relevant marker genes for image-based spatial transcriptomics data.

Key Features:

• Spatial Vector Creation: Functions create spatial vectors from cell and transcript coordinates to serve as inputs for marker gene detection.
• Permutation Testing: Marker genes are detected by parallel permutation testing for single-sample studies.
• Linear Modeling: Marker genes are detected by building a linear model for every gene, which can account for multiple samples and background noise.

Scientific Applications:

• Spatial Transcriptomics Marker Gene Identification: Identifies cluster-specific marker genes in image-based spatial transcriptomics datasets.
• Multi-sample Analysis: Enables marker gene detection across multiple samples while controlling for background noise.

Methodology:

Marker gene detection employs two approaches: permutation testing implemented in parallel for single-sample studies, and linear model construction per gene to account for multiple samples and background noise.