OSAT

OSAT allocates samples into experimental batches to minimize batch effects and balance biological groups and confounding factors in genomic studies, and is available as a Bioconductor package.

Key Features:

• Automated Sample-to-Batch Allocation: Automates assignment of collected samples to batches using algorithmic allocation to reduce manual allocation bias.
• Optimization of Distribution: Optimizes distribution of samples across multiple batches to minimize confounding correlations between batch and biological variables.
• Handling Imbalanced Data: Manages incomplete or unbalanced sample collections to preserve experimental design robustness.
• Homogeneous Distribution of Confounders: Ensures confounding factors are evenly distributed across batches to limit batch-related variability.

Scientific Applications:

• Experimental design for genomic studies: Facilitates allocation in large-scale genomic experiments to reduce batch effects and improve reproducibility.
• Analysis of biological processes and disease mechanisms: Supports generation of reliable data for detecting biological signals and disease-associated variation by minimizing technical confounding.

Methodology:

Algorithms analyze sample distributions using predefined criteria for biological groups and confounding factors and use that analysis to perform automated assignment of samples to produce batches as homogeneous as possible with respect to those variables.