GOgetter: A pipeline for summarizing and visualizing GO slim annotations for plant genetic data

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Functional annotation of genes is essential for genomic analysis.
• Gene Ontology (GO) provides a hierarchical framework for describing gene functions.
• Summarizing GO annotations with GO slims is crucial for characterizing gene sets but often impractical manually.

Purpose of the Study:

• To develop an automated pipeline for obtaining, summarizing, and visualizing GO slim categories.
• To facilitate the characterization of overall gene function within a dataset.

Main Methods:

• The GOgetter pipeline utilizes bash and Python scripts.
• It processes input FASTA files of nucleotide gene sequences.
• Outputs include gene-to-reference gene model hits, associated GO terms, and GO slim summaries/visualizations.

Main Results:

• The pipeline identifies the best hit for each input gene.
• It retrieves all GO terms and annotations linked to these hits.
• Generates summarized and visualized GO slim categories for the entire dataset.

Conclusions:

• GO annotations serve as a universal language for gene function description.
• GOgetter offers a fast and user-friendly method for GO slim analysis.
• The pipeline aids in statistical analysis and downstream querying of gene functional data.