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FunGAP: Fungal Genome Annotation Pipeline using evidence-based gene model evaluation

Author:
Min, Byoungnam, Grigoriev, Igor V., Choi, In-Geol
Source:
Bioinformatics 2017 v.33 no.18 pp. 2936-2937
ISSN:
1460-2059
Subject:
bioinformatics, computer software, fungi, genes, genome assembly, models, prediction
Abstract:
Motivation: Successful genome analysis depends on the quality of gene prediction. Although fungal genome sequencing and assembly have become trivial, its annotation procedure has not been standardized yet. Results: FunGAP predicts protein-coding genes in a fungal genome assembly. To attain high-quality gene models, this program runs multiple gene predictors, evaluates all predicted genes, and assembles gene models that are highly supported by homology to known sequences. To do this, we built a scoring function to estimate the congruency of each gene model based on known protein or domain homology. Availability and implementation: FunGAP is written in Python script and is available in GitHub (https://github.com/CompSynBioLab-KoreaUniv/FunGAP). This software is freely available only for noncommercial users. Contact: igchoi@korea.ac.kr Supplementary information:Supplementary data are available at Bioinformatics online.
Agid:
6248890