Normalyzer

Normalyzer evaluates normalization methods for high-throughput omics data to identify approaches that mitigate systematic biases and improve quantitative accuracy in downstream analyses.

Key Features:

• Multiple Normalization Methods: Implements a suite of 12 different normalization methods for comparative assessment.
• Comparative Evaluation: Generates reports with quantitative and qualitative plots to compare the effectiveness of each normalization method on a dataset.
• Case Study Demonstrations: Provides three case studies in quantitative proteomics and transcriptomics illustrating how normalization choices influence downstream interpretation.

Scientific Applications:

• Normalization selection for omics datasets: Supports selection of appropriate normalization strategies to mitigate systematic biases in genomics, proteomics, and transcriptomics data.

Methodology:

Implemented as an R package that applies each of the 12 specified normalization methods to the input dataset and produces detailed reports with quantitative and qualitative plots.