HarmonizR

HarmonizR enables batch effect removal by ComBat or Limma while preserving maximum data through intelligent handling of missing values.

Key Features:

• Missing Value Handling: Dissects input matrices into smaller matrices with sufficient data to feed the ComBat or limma algorithm.
• Matrix Reconstruction: Returns adjusted data as a rebuilt matrix after batch correction.
• Minimal Data Loss: Maximizes data availability by making as much data available as possible.

Scientific Applications:

• Batch Effect Correction: Prepares data for proper batch effect removal using ComBat or Limma in proteomics and other omics datasets with missing values.

Methodology:

The implementation dissects the input matrix into smaller matrices with sufficient data to feed the ComBat or limma algorithm, then rebuilds the adjusted data into a single matrix.