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

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Abstract

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-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/.

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  1. Now published in GigaScience doi: 10.1093/gigascience/giy096

    Sung-Huan Yu 1Institute of Molecular Infection Biology (IMIB), University of Würzburg, 97080 Würzburg, GermanyFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Sung-Huan YuJörg Vogel 1Institute of Molecular Infection Biology (IMIB), University of Würzburg, 97080 Würzburg, GermanyFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Jörg VogelKonrad U. Förstner 1Institute of Molecular Infection Biology (IMIB), University of Würzburg, 97080 Würzburg, Germany2Core Unit Systems Medicine, University of Würzburg, 97080 Würzburg, GermanyFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Konrad U. FörstnerFor correspondence: konrad.foerstner@uni-wuerzburg.de

    A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giy096 ), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

    These peer reviews were as follows:

    Reviewer 1: http://dx.doi.org/10.5524/REVIEW.101337 Reviewer 2: http://dx.doi.org/10.5524/REVIEW.101338 Reviewer 3: http://dx.doi.org/10.5524/REVIEW.101339