4.7 Article

AGORA: organellar genome annotation from the amino acid and nucleotide references

Journal

BIOINFORMATICS
Volume 34, Issue 15, Pages 2661-2663

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bty196

Keywords

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Funding

  1. National Research Foundation (NRF) of Korea - Ministry of Science, ICT & Future Planning, Basic Science Research Program [MSIP] [NRF-2016R1C1B1007929]
  2. Ministry of Education [2015R1D1A1A01057899, 2016R1D1A1A09919318]
  3. 2017 Hongik University Research Fund

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Next-generation sequencing (NGS) technologies have led to the accumulation of high-throughput sequence data from various organisms in biology. To apply gene annotation of organellar genomes for various organisms, more optimized tools for functional gene annotation are required. Almost all gene annotation tools are mainly focused on the chloroplast genome of land plants or the mitochondrial genome of animals. We have developed a web application AGORA for the fast, user-friendly and improved annotations of organellar genomes. Annotator for Genes of Organelle from the Reference sequence Analysis (AGORA) annotates genes based on a basic local alignment search tool (BLAST)-based homology search and clustering with selected reference sequences from the NCBI database or user-defined uploaded data. AGORA can annotate the functional genes in almost all mitochondrion and plastid genomes of eukaryotes. The gene annotation of a genome with an exon-intron structure within a gene or inverted repeat region is also available. It provides information of start and end positions of each gene, BLAST results compared with the reference sequence and visualization of gene map by OGDRAW. Availability and implementation: Users can freely use the software, and the accessible URL is https://bigdata.dongguk.edu/gene_project/AGORA/. The main module of the tool is implemented by the python and php, and the web page is built by the HTML and CSS to support all browsers. Contact: gangman@dongguk.edu Supplementary information: Supplementary data are available at Bioinformatics online.

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