• search hit 10 of 14
Back to Result List

ANNOgesic: a Swiss army knife for the RNA-seq based annotation of bacterial/archaeal genomes

Please always quote using this URN: urn:nbn:de:bvb:20-opus-178942
  • To understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or noncoding RNAs, are harder to detect. RNA sequencing (RNA-seq) has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-seq data in order to generate high-resolutionTo understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or noncoding RNAs, are harder to detect. RNA sequencing (RNA-seq) has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-seq data in order to generate high-resolution annotations is challenging, time consuming, and requires numerous steps. We have constructed a powerful and modular tool called ANNOgesic that provides the required analyses and simplifies RNA-seq-based bacterial and archaeal genome annotation. It can integrate data from conventional RNA-seq and differential RNA-seq and predicts and annotates numerous features, including small noncoding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pypi.org/project/ANNOgesic/.show moreshow less

Download full text files

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Metadaten
Author: Sung-Huan YuORCiD, Jörg VogelORCiD, Konrad U. FörstnerORCiD
URN:urn:nbn:de:bvb:20-opus-178942
Document Type:Journal article
Faculties:Medizinische Fakultät / Institut für Molekulare Infektionsbiologie
Language:English
Parent Title (English):GigaScience
Year of Completion:2018
Volume:7
Source:GigaScience, 7, 2018. DOI: 10.1093/gigascience/giy096
DOI:https://doi.org/10.1093/gigascience/giy096
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:RNA-seq; genome annotation; transcriptomics
Release Date:2019/04/05
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2018
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International