Prokaryotic contig annotation pipeline server: Web application for a prokaryotic genome annotation pipeline based on the shiny app package

Byeonghyeok Park, Min Jeong Baek, Byoungnam Min, In-Geol Choi

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Genome annotation is a primary step in genomic research. To establish a light and portable prokaryotic genome annotation pipeline for use in individual laboratories, we developed a Shiny app package designated as "P-CAPS" (Prokaryotic Contig Annotation Pipeline Server). The package is composed of R and Python scripts that integrate publicly available annotation programs into a server application. P-CAPS is not only a browser-based interactive application but also a distributable Shiny app package that can be installed on any personal computer. The final annotation is provided in various standard formats and is summarized in an R markdown document. Annotation can be visualized and examined with a public genome browser. A benchmark test showed that the annotation quality and completeness of P-CAPS were reliable and compatible with those of currently available public pipelines.

Original languageEnglish
Pages (from-to)917-922
Number of pages6
JournalJournal of Computational Biology
Volume24
Issue number9
DOIs
Publication statusPublished - 2017 Sep 1

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Web Application
Application programs
Annotation
Genome
Servers
Server
Pipelines
Genes
Boidae
Benchmarking
Microcomputers
Personal computers
Light
Python
Research
Personal Computer
Genomics
Completeness
Integrate
Benchmark

Keywords

  • gene prediction
  • microbial genome annotation
  • R package
  • web application

ASJC Scopus subject areas

  • Modelling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

Prokaryotic contig annotation pipeline server : Web application for a prokaryotic genome annotation pipeline based on the shiny app package. / Park, Byeonghyeok; Baek, Min Jeong; Min, Byoungnam; Choi, In-Geol.

In: Journal of Computational Biology, Vol. 24, No. 9, 01.09.2017, p. 917-922.

Research output: Contribution to journalArticle

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