NanoStringNorm

NanoStringNorm normalizes NanoString nCounter gene expression data and diagnoses technical variation to enable reliable downstream statistical analyses.

Key Features:

• Extensible environment: Provides a framework for comparing different normalization methods and developing new algorithms.
• Integrated diagnostics: Generates diagnostics at both gene and sample levels to identify dataset issues.
• Technical artifact removal: Performs normalization and removal of systematic inter-sample technical artifacts arising from sample preservation, extraction, and platform variability.
• Comprehensive diagnostics: Produces visual and numeric diagnostics for thorough dataset quality assessment.
• Robust validation: Includes unit tests that guarantee numerical accuracy of processing steps.

Scientific Applications:

• Normalization of NanoString nCounter data: Pre-processes raw NanoString counts to correct technical variation in measurements of nucleic acid abundances.
• Analysis of challenging sample types: Applicable to studies involving archival formalin-fixed paraffin-embedded (FFPE) tissues and other problematic specimens.
• Preparation for downstream statistical analysis: Produces normalized data suitable for subsequent statistical and comparative analyses.

Methodology:

Implements pre-processing within the R environment by performing normalization and technical artifact removal, providing gene- and sample-level visual and numeric diagnostics, supporting comparison of normalization methods and algorithm development, and including unit tests for numerical validation.