GOThresher

GOThresher removes annotation biases from protein function annotation datasets to improve the representativeness of Gene Ontology (GO)-based annotations for biological interpretation and machine-learning model training.

Key Features:

• Bias Identification: Identifies disproportionate representation of specific Gene Ontology (GO) terms within protein function annotation datasets.
• Bias Removal: Applies methods to remove or adjust biased annotations, refining datasets for downstream analyses.
• Statistical Adjustment: Implements statistical methods to detect and correct imbalances in GO term representation.

Scientific Applications:

• Enhanced Annotation Quality: Produces datasets with reduced GO-term overrepresentation to support more accurate biological interpretation.
• Machine Learning Model Training: Provides less-biased training data to improve reliability and performance of protein function prediction models.
• Functional Genomics Workflows: Mitigates biases arising from high-throughput experimental annotations when integrated into research workflows.

Methodology:

Analyzes protein function annotation datasets to identify overrepresented Gene Ontology (GO) terms and applies statistical methods to adjust or remove these imbalances.