SpaceTrooper

SpaceTrooper performs quality control analysis of image-based spatial data using data-driven generalized linear model (GLM) strategies to detect low-quality cells in imaging-based spatial transcriptomics and proteomics datasets.

Key Features:

• GLM-based quality control: Implements a generalized linear model strategy for the detection of low-quality cells in imaging-based spatial transcriptomics and proteomics data.
• QC metrics computation: Computes quality control metrics for image-based spatial data.
• Outlier detection: Identifies outlier cells through data-driven GLM models.
• Exploration plots: Generates plots for exploratory analysis of image-based spatial data.
• Polygon visualization: Implements several plots for the visualization of imaging-based polygons through the ggplot2 package.

Scientific Applications:

• Spatial transcriptomics quality control: Detects low-quality cells in imaging-based spatial transcriptomics datasets.
• Spatial proteomics quality control: Detects low-quality cells in imaging-based spatial proteomics datasets.
• Spatial data exploration: Supports exploratory visualization of imaging-based spatial data and cell polygons.

Methodology:

SpaceTrooper uses data-driven generalized linear model (GLM) models for quality control analysis of image-based spatial data.