standR

standR enables end-to-end analysis of Nanostring GeoMx Digital Spatial Profiler (DSP) spatial transcriptomics data through quality control workflows that account for technical variability and complex experimental designs.

Key Features:

• Data Inspection: Provides functions for examining GeoMx DSP datasets prior to downstream analysis.
• Quality Control: Implements experiment-specific investigations into technical variation within spatial transcriptomics data.
• Normalization: Performs normalization of gene expression measurements from GeoMx DSP experiments.
• Batch Correction: Adjusts for batch effects and technical variability across complex experimental designs.
• Evaluation with Visualizations: Generates informative visualizations to assess data quality and analytical performance.
• SpatialExperiment Integration: All functions are built on the SpatialExperiment object for compatibility with Bioconductor spatial transcriptomics packages.

Scientific Applications:

• Spatial Transcriptomics Analysis: Supports quantitative spatially resolved measurement of the transcriptome in normal and diseased tissues.
• Technical Variability Assessment: Enables in-depth investigation of technical variation to improve accuracy and reliability of GeoMx DSP data analysis.
• Biological Insight Discovery: Enhances statistical power to develop in-depth insights into tissue biology through carefully designed quality control workflows.

Methodology:

standR is implemented as an R/Bioconductor package with all functions built on the SpatialExperiment object class.