HEMDAG-package {HEMDAG}

HEMDAG: Hierarchical Ensemble Methods for Directed Acyclic Graphs

Description

The HEMDAG package:

• provides an implementation of several Hierarchical Ensemble Methods (HEMs) for Directed Acyclic Graphs (DAGs);

• reconciles flat predictions with the topology of the ontology;

• can enhance predictions of virtually any flat learning methods by taking into account the hierarchical relationships between ontology classes;

• provides biologically meaningful predictions that obey the true-path-rule, the biological and logical rule that governs the internal coherence of biomedical ontologies;

• is specifically designed for exploiting the hierarchical relationships of DAG-structured taxonomies, such as the Human Phenotype Ontology (HPO) or the Gene Ontology (GO), but can be safely applied to tree-structured taxonomies as well (as FunCat), since trees are DAGs;

• scales nicely both in terms of the complexity of the taxonomy and in the cardinality of the examples;

• provides several utility functions to process and analyze graphs;

• provides several performance metrics to evaluate HEMs algorithms;

A comprehensive tutorial showing how to apply HEMDAG to real case bio-medical case studies is available at https://hemdag.readthedocs.io.

Details

The HEMDAG package implements the following Hierarchical Ensemble Methods for DAGs:

1. HTD-DAG: Hierarchical Top Down (htd);

2. GPAV-DAG: Generalized Pool-Adjacent Violators, Burdakov et al. (gpav);

3. TPR-DAG: True-Path Rule (tpr.dag);

4. DESCENS: Descendants Ensemble Classifier (tpr.dag);

5. ISO-TPR: Isotonic-True-Path Rule (tpr.dag);

6. Max, And, Or: Heuristic Methods, Obozinski et al. (obozinski.heuristic.methods);

Author(s)

Marco Notaro^1 (https://orcid.org/0000-0003-4309-2200);
Alessandro Petrini^1 (https://orcid.org/0000-0002-0587-1484);
Giorgio Valentini^1 (https://orcid.org/0000-0002-5694-3919);

Maintainer: Marco Notaro [e-mail]

^1 AnacletoLab, Computational Biology and Bioinformatics Laboratory, Computer Science Department, University of Milan, Italy

References

Marco Notaro, Max Schubach, Peter N. Robinson and Giorgio Valentini, Prediction of Human Phenotype Ontology terms by means of Hierarchical Ensemble methods, BMC Bioinformatics 2017, 18(1):449, doi: 10.1186/s12859-017-1854-y