pathMED

pathMED facilitates precision medicine studies with omics data by calculating geneset scores for individual samples, training machine learning models, and predicting clinical features on new data.

Key Features:

• Geneset Scoring: Calculates geneset scores for individual samples using several methods.
• Machine Learning Training: Uses calculated scores to train machine learning models for predicting clinical features on new data.
• Model Selection and Hyperparameter Tuning: Evaluates several machine learning methods to select the best method based on internal validation and tunes hyperparameters.
• Performance Evaluation: Returns performance metrics and a ready-to-use model to predict outcomes for new patients.

Scientific Applications:

• Precision Medicine Studies: Supports precision medicine research using omics data such as transcriptomics.
• Clinical Feature Prediction: Predicts clinical features and patient outcomes from molecular data.

Methodology:

Several machine learning methods are evaluated with internal validation for model selection and hyperparameter tuning.