Fast Mode

Fast Mode

CASSIA's Fast Mode offers a streamlined, one-line solution for running the complete analysis pipeline. This mode combines annotation, scoring, and annotation boost in a single function call, using optimized default parameters.

Basic Usage

runCASSIA_pipeline(
    output_file_name = "my_analysis",
    tissue = "brain",
    species = "human",
    marker = marker_data,
    max_workers = 4
)

Full Parameter Options

runCASSIA_pipeline(
    # Required parameters
    output_file_name,     # Base name for output files
    tissue,               # Tissue type (e.g., "brain", "blood")
    species,              # Species (e.g., "human", "mouse")
    marker,               # Marker file from findallmarker, path or the data obejct
    
    # Optional parameters with defaults
    max_workers = 4,      # Number of parallel workers
    
    # Model configurations
    annotation_model = "gpt-4o",             # Model for annotation
    annotation_provider = "openai",         # Provider for annotation
    score_model = "anthropic/claude-3.5-sonnet",  # Model for scoring
    score_provider = "openrouter",         # Provider for scoring
    annotationboost_model="anthropic/claude-3.5-sonnet", #Model for annotation boost
    annotationboost_provider="openrouter", #Provider for annotation boost
    
    # Analysis parameters
    score_threshold = 75,     # Minimum acceptable score
    additional_info = NULL    # Additional context information
)

Output Files

The pipeline generates:

  1. Initial annotation results
  2. Quality scores and reasoning
  3. Summary report
  4. Annotation boost report

Performance Tips

  • For optimal performance, adjust max_workers based on your system's CPU cores
  • Use additional_info to provide relevant experimental context
  • Monitor score_threshold to balance stringency with throughput

Next we introduce each function in detail...

Setting Up CASSIASingle Cluster Analysis