OG

"OG" refers to a methodology and high-throughput pipeline designed to ensure hierarchical consistency of orthologous groups (OGs) across different taxonomic levels. Orthologous groups consist of genes that share a last common ancestor (LCA) and can include both orthologous and paralogous genes. A hierarchy of OGs connects more general, distant OGs to more recent, fine-grained ones, covering multiple levels of the Tree of Life. However, large-scale inference of such hierarchies can encounter inconsistencies due to various factors, including genetic signal confusion or algorithmic limitations, which can impact their utility for functional annotation and other applications.

Key Features and Functionalities:

- Hierarchical Consistency: This methodology ensures the consistency of OG hierarchies across taxonomic levels, addressing inconsistencies such as the temporal positioning of duplication events.

- Subsampling and Reconciliation: The methodology involves subsampling the protein space of OG members and performing gene tree-species tree reconciliation for each subset. This approach simplifies the complex task of building and reconciling extensive phylogenies.

- High-throughput Pipeline: The methodology is implemented in a high-throughput pipeline, making it suitable for processing large datasets efficiently.

- Application to eggNOG Database: The pipeline has been applied to the eggNOG database, demonstrating its practical utility and effectiveness in improving the consistency of OG hierarchies.

- Validation with Protein Domain Definitions: Independent protein domain definitions were used to validate the performance of the consistency pipeline, indicating its reliability and accuracy.