GEDI

GEDI integrates transcriptomic datasets from microarrays and next-generation sequencing to perform probe re-annotation, remove batch effects, and enable cross-platform data integration for downstream comparative analyses.

Key Features:

• Integration Across Platforms: Supports integration of data from Affymetrix and Agilent microarrays and RNA sequencing (NGS) datasets.
• Re-annotation Automation: Automates probe re-annotation to harmonize feature identifiers across platforms.
• Batch Effect Removal: Implements batch effect removal algorithms to correct technical variation between datasets.
• Batch Effect Removal Verification: Uses Principal Component Analysis (PCA) to verify effective removal of batch effects.
• Data Integration Validation: Validates integrated data using a logistic regression model with forward stepwise feature selection.
• Streamlined Workflow: Provides four core functions that automate re-annotation and batch effect removal within the integration pipeline.
• Comprehensive Pipeline: Combines re-annotation, batch effect removal, and statistical verification into a single end-to-end pipeline.

Scientific Applications:

• Cross-study integration: Combines multiple transcriptomic datasets to increase statistical power for differential expression and comparative analyses.
• Novel transcript and gene discovery: Facilitates discovery of novel transcripts and genes by integrating heterogeneous transcriptomic datasets.
• Empirical demonstration: Applied to the integration of five bovine endometrial transcriptomic datasets from the NCBI Gene Expression Omnibus.

Methodology:

Automates probe re-annotation and batch effect removal, employs Principal Component Analysis (PCA) for verification, and validates integration using logistic regression with forward stepwise feature selection while leveraging existing R packages.