oggmap: a Python package to extract gene ages per orthogroup and link them with single-cell RNA data

Area of Science:

• Genomics
• Evolutionary Biology
• Bioinformatics

Background:

• Single-cell RNA sequencing (scRNA-seq) is advancing cell atlases for model organisms.
• The need for comprehensive cell atlases is expanding to non-model species.
• Understanding gene evolution is crucial for interpreting scRNA-seq data.

Purpose of the Study:

• To introduce oggmap, a Python package for generating ortholog gene age maps (orthomaps).
• To facilitate the integration of evolutionary information into single-cell transcriptomics.
• To enhance the analysis of cell types by considering their evolutionary history.

Main Methods:

• Utilizes OrthoFinder for orthogroup identification and gene age extraction.
• Supports gene family data from resources like eggNOG and PLAZA.
• Integrates with the Python Scanpy toolkit for gene age-weighted expression analysis.

Main Results:

• Provides gene age data for over a thousand eukaryotic species.
• Enables visualization of gene categories (e.g., age class, nucleotide diversity) and expression profiles.
• Facilitates evolutionary contextualization of scRNA-based cell type assignments.

Conclusions:

• oggmap simplifies the creation of evolutionary metrics for scRNA-seq analysis.
• The package supports diverse evolutionary analyses beyond single transcriptome evolutionary indices.
• oggmap enhances the biological interpretation of cell types by integrating evolutionary data.