multistateQTL

multistateQTL provides a collection of tools for analyzing multi-state QTL data with a focus on visualization and interpretation.

Key Features:

• Missing Data Handling: Functions remove or impute missing data in multi-state QTL datasets.
• Significance Detection: Functions identify significant associations in multi-state QTL data.
• Feature Categorization: Functions categorise features into global, multi-state or unique classes.
• Data Structure: Analysis results are stored in a QTLExperiment object based on the SummarisedExperiment framework.

Scientific Applications:

• Multi-state QTL Analysis: Enables various analyses of multi-state QTL data across biological conditions or states.
• QTL Data Visualization: Supports visualization of multi-state QTL analysis results for biological interpretation.

Methodology:

The package implements functions for data preprocessing, significance testing, and feature classification, with results organized within the QTLExperiment object structure based on SummarisedExperiment.