GOMAP

Gene Ontology Meta Annotator for Plants

Making a genome sequence accessible and useful involves three basic steps: genome assembly, structural annotation, and functional annotation. The quality of data generated at each step influences the accuracy of inferences that can be made, with high- quality analyses produce better datasets resulting in stronger hypotheses for downstream experimentation. genome sequence

Gene Ontology Meta Annotator for Plants (GOMAP) is a high-throughput pipeline to annotate GO terms to plant protein sequences in a high-confidence and reproducible manner. It combines sequence-similarity, domain-presence and mixed-method based approaches and we are currently applying it to the reference genomes of several agriculturally important plants (maize, wheat, rice, cotton, soybean). All generated annotation datasets as well as the source code are publicly available.

For more information on how the pipeline works as well as instructions on how to run it yourself, please check out the documentation on GitHub.

GOMAP was developed from maize-GAMER (Publication), a collaborative project to improve the status of gene functional annotation in maize.

maize-GAMER

maize-GAMER is a collaborative project to improve the status of gene functional annotation in maize. The project has three main areas of focus, namely

Design a pipeline for the functional annotation of maize genes.
Use manually curated test data to evaluate the annotations and generate a best subset of annotations for use
Design a user friendly review system for the community to provide feedback and endorsements of the annotations

Predicting Annotations

GO annotations are generated using three different approaches in the pipeline.

Sequence similarity to Arabidopsis (TAIR) and existing plant genes with curated GO annotations.
InterproScan to detect protein domains which have GO terms annotated to them.
CAFA (Critical Assessment of Functional Annotation) tools (Argot2, FANNGO, PANNZER) that use a combination of machine learning and statistics to predict GO terms for input genes

These annotations will be compared to available GO annotations for maize from Gramene. Gramene uses the Ensembl Compara pipeline to generate GO annotations. RBH – Reciprocal Best Hit

Evaluating Annotations

evaluation pipeline

Represents the part of the pipeline which is used to evaluate the annotations by calculating and comparing the performance measures.

Test datasets is comprised of Gold Standard - manually curated annotations from MaizeGDB. About 4% of the maize protein coding genes are represented in this test dataset.
Protein-centric evaluation metrics from the CAFA project are currently being used to evaluate different tools.
- Precision (PR) is the mean of the proportion of correctly predicted annotations for a given protein compared to the total number of predictions
- Recall (RC) is the mean proportion of correctly predicted annotations for a given protein compared to the total number of annotations in the test dataset for the given protein.
- F-score is a single value which reflects a tool’s accuracy, and is calculated from RP and RC

Reviewing Annotations

Represents the outline of the Review system which will be implemented at the end of the evaluation step.

Basic View will have minimal information necessary for subject experts to review their gene(s) of their choice quickly.
Evidence View will allow users to look at the tools that support a particular GO annotation. Each tool supporting the particular annotation will have a simple graphic showing the details of the annotations. E.g., Sequence similarity based methods will have a simple diagram representing the representative target, coverage, identity, and E-value of a given BLAST hit.

All this data will be made available for download for downstream analysis of you own experiments. Non-reviewed annotations will be made available as soon as the evaluation of the results from the pipeline are completed. Reviewed annotations will be made available after the release of the tool to the maize community and sufficient time has been given for accumulation of community effort for revision of the Non-reviewed annotations.