PEA-m6A is an ensemble learning framework for predicting m6A modifications at regional-scale. PEA-m6A consists of four modules: Sample Preparation, Feature Encoding, Model Development and Model Assessment, each of which contains a comprehensive collection of functions with pre-specified parameters available.
The PEA-m6A adopted an advanced packaging strategy, containing all computational programs, newly developed scripts, and dependencies.