ANNOgesic - A Swiss army knife for the RNA-Seq based annotation of bacterial/archaeal genomes
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README.rst

About ANNOgesic

ANNOgesic is the swiss army knife for RNA-Seq based annotation of bacterial/archaeal genomes.

It is a modular, command-line tool that can integrate different types of RNA-Seq data based on dRNA-Seq (differential RNA-Seq) or RNA-Seq protocols that inclusde transcript fragmentation to generate high quality genome annotations. It can detect genes, CDSs/tRNAs/rRNAs, transcription starting sites (TSS) and processing sites, transcripts, terminators, untranslated regions (UTR) as well as small RNAs (sRNA), small open reading frames (sORF), circular RNAs, CRISPR related RNAs, riboswitches and RNA-thermometers. It can also perform RNA-RNA and protein-protein interactions prediction. Furthermore, it groups genes into operons and sub-operons and reveal promoter motifs. It can also allocate GO term and subcellular localization to genes. Several of ANNOgesic features are new implementations while other build on well known third-party tools for which it offers adaptive parameter-optimizations. Additionally, numerous visualization and statistics help the user to quickly evaluat feature predictions resulting from an ANNOgesic analysis. The tool was heavily tested with several RNA-Seq data set from bacterial as well as archaeal samples.

Documentation

Documentation can be found on here.

Installation

Pip3

If you have all the requirements installed, installation can be done by using pip3.

With root permission:

$ pip3 install ANNOgesic

without root permission

$ pip3 install --user ANNOgesic

If you want to know the requirement, please refer to Documentation.

Docker and Singularity

In order to solve the issue of installing the dependencies, a Docker image of ANNOgesic is provided in Docker Hub. The image can be pulled by using Docker or Singularity. Moreover, the users can build an Docker image from the Dockerfile by themselves. For the details, please check the documentation.

Github

The alternative way for installing ANNOgesic is directly clone the Git repository.

$ git clone https://github.com/Sung-Huan/ANNOgesic.git

or

$ git clone git@github.com:Sung-Huan/ANNOgesic.git

In order to make ANNOgesic runnable, we should create a soft link of annogesiclib in bin.

$ cd ANNOgesic/bin
$ ln -s ../annogesiclib .

Then, you can run ANNOgesic via specifying the installed path if all the requirements are setup properly.

Arguments

usage: annogesic [-h] [--version]
                 {create,get_input_files,update_genome_fasta,annotation_transfer,
                  tss_ps,optimize_tss_ps,terminator,transcript,utr,srna,sorf,
                  promoter,operon,circrna,go_term,srna_target,snp,ppi_network,
                  localization,riboswitch_thermometer,crispr,merge_features,
                  screenshot,colorize_screenshot_tracks}
                 ...

positional arguments:
  {create,get_input_files,update_genome_fasta,annotation_transfer,tss_ps,
   optimize_tss_ps,terminator,transcript,utr,srna,sorf,promoter,operon,circrna,
   go_term,srna_target,snp,ppi_network,localization,riboswitch_thermometer,
   crispr,merge_features,screenshot,colorize_screenshot_tracks}
                        commands
    create              Create a project
    get_input_files     Get required files. (i.e. annotation files, fasta
                        files)
    update_genome_fasta
                        Get fasta files of query genomes if the query
                        sequences do not exist.
    annotation_transfer
                        Transfer the annotations from a closely related
                        species genome to a target genome.
    tss_ps              Detect TSSs or processing sites.
    optimize_tss_ps     Optimize TSSs or processing sites based on manual
                        detected ones.
    terminator          Detect rho-independent terminators.
    transcript          Detect transcripts based on coverage file.
    utr                 Detect 5'UTRs and 3'UTRs.
    srna                Detect intergenic, antisense and UTR-derived sRNAs.
    sorf                Detect expressed sORFs.
    promoter            Discover promoter motifs.
    operon              Detect operons and sub-operons.
    circrna             Detect circular RNAs.
    go_term             Extract GO terms from Uniprot.
    srna_target         Detect sRNA-mRNA interactions.
    snp                 Detect SNP/mutation and generate fasta file if
                        mutations were found.
    ppi_network         Detect protein-protein interactions suported by
                        literature.
    localization        Predict subcellular localization of proteins.
    riboswitch_thermometer
                        Predict riboswitches and RNA thermometers.
    crispr              Predict CRISPR related RNAs.
    merge_features      Merge all features to one gff file.
    screenshot          Generate screenshots for selected features using IGV.
    colorize_screenshot_tracks
                        Add color information to screenshots (e.g. useful for
                        dRNA-Seq based TSS and PS detection. It only works
                        after running "screenshot" (after running batch
                        script).

optional arguments:
  -h, --help            show this help message and exit
  --version, -v         show version

Citation

SH Yu, J. Vogel, KU Förstner. 2018, GigaScience, DOI:10.1093/gigascience/giy096, PMID:30169674.

License

ISC (Internet Systems Consortium license ~ simplified BSD license) - see LICENSE

Contact

If you have any questions, please contact Sung-Huan Yu