Supporting data for "ANNOgesic: A Swiss army knife for the RNA-Seq based annotation of bacterial/archaeal genomes"

Dataset type: Software, Transcriptomic
Data released on July 17, 2018

Yu SH; Vogel J; Förstner KU (2018): Supporting data for "ANNOgesic: A Swiss army knife for the RNA-Seq based annotation of bacterial/archaeal genomes" GigaScience Database. http://dx.doi.org/10.5524/100481

DOI10.5524/100481

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 non-coding RNAs are harder to detect. 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 different 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 dRNA-Seq, predicts and annotates numerous features, including small non-coding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pypi.org/project/ANNOgesic/.

Additional details

Read the peer-reviewed publication(s):

Yu, S.-H., Vogel, J., & Förstner, K. U. (2018). ANNOgesic: a Swiss army knife for the RNA-seq based annotation of bacterial/archaeal genomes. GigaScience, 7(9). doi:10.1093/gigascience/giy096

Additional information:

https://github.com/Sung-Huan/ANNOgesic

https://pypi.org/project/ANNOgesic/

http://annogesic.readthedocs.io/en/latest/subcommands.html

http://annogesic.readthedocs.io/en/latest/required.html

https://hub.docker.com/r/silasysh/annogesic/





File NameSample IDData TypeFile FormatSizeRelease Date 
SoftwareTAR561.42 KB2018-07-02
SoftwareUNKNOWN292.74 KB2018-07-02
GitHub archivearchive640.53 KB2018-07-02
ReadmeTEXT2.13 KB2018-07-02
Displaying 1-4 of 4 File(s).
Funding body Awardee Award ID Comments
Deutsche Forschungsgemeinschaft J Vogel CRC-TRR34 Transregio 34

Code Ocean:

Date Action
July 17, 2018 Dataset publish
July 24, 2018 External Link added : https://doi.org/10.24433/CO.6eae18de-4c12-4245-86fc-e9a447d22c68
July 24, 2018 External Link updated : CO.6eae18de-4c12-4245-86fc-e9a447d22c68
July 24, 2018 External Link updated :
July 24, 2018 External Link updated :
August 22, 2018 Manuscript Link added : 10.1093/gigascience/giy096