ANNOgesic 0.4.1

A bacterial transcriptome annotation pipeline based on RNA-Seq

About ANNOgesic

ANNOgesic is a bacterial transcriptome annotation pipeline based on RNA-Seq. ANNOgesic covers different aspects of the genome annotation. In order to get the best results, ANNOgesic also can optimize the parameters of some tools. ANNOgesic can automatically generate high-quality annotation information for query strains. Moreover, it is modular and its subcommands can be separately used. ANNOgesic integrates six main classes of annotations. i) Reference genome improvement: SNP/mutation calling, Sequence modification and annotation transfer. ii) Transcript boundary: TSS, transcript, terminator, UTR and processing site. iii) sRNA and sORF: sRNA, sORF and sRNA target prediction. iv) Functional related features: protein-protein interaction networks, Gene ontology and subcellular localization. v) Promoter and operon: promoter motifs and operon with sub-operon. vi) Other features: circular RNA, CRISPR, RNA thermometer and riboswitch.

Documentation

Documentation can be found on here.

Installation

Short version (if you have all the requirements installed):

$ pip3 install ANNOgesic

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

Arguments

usage: annogesic [-h] [--version]
                 {create,get_input_files,get_target_fasta,annotation_transfer,tsspredator,optimize_tsspredator,color_png,terminator,transcript_assembly,utr,srna,sorf,promoter,operon,circrna,go_term,srna_target,snp,ppi_network,subcellular_localization,riboswitch_thermometer,crispr,merge_features,screenshot}
                 ...

positional arguments:
  {create,get_input_files,get_target_fasta,annotation_transfer,tsspredator,optimize_tsspredator,color_png,terminator,transcript_assembly,utr,srna,sorf,promoter,operon,circrna,go_term,srna_target,snp,ppi_network,subcellular_localization,riboswitch_thermometer,crispr,merge_features,screenshot}
                        commands
    create              Create a project
    get_input_files     Get required files. (i.e. annotation files, fasta
                        files)
    get_target_fasta    Get target fasta.
    annotation_transfer
                        Run RATT to transfer the annotation files from
                        reference to target.
    tsspredator         Run TSSpredator to predict TSSs or processing sites.
    optimize_tsspredator
                        Optimize TSSpredator based on (partial)manual detect
                        one.
    color_png           Generating color screenshots of TSS or processing
                        site. It only works after running batch script.
    terminator          Detect Terminators.
    transcript_assembly
                        Run transcriptome assembly for detecting transcripts.
    utr                 Run UTR detection to detect 5'UTR and 3'UTR.
    srna                Run sRNA detection to detect sRNA candidates.
    sorf                Run sORF detection to detect sORF candidates which has
                        expression.
    promoter            Run MEME to dicover promoter.
    operon              Detect operon and combine features together.
    circrna             Detect circular RNA.
    go_term             Extract and find Go terms.
    srna_target         sRNA target prediction.
    snp                 Detection of SNP of transcripts.
    ppi_network         Generate protein-protein interaction with literature
                        supported.
    subcellular_localization
                        Prediction of subcellular localization of genomic CDS.
    riboswitch_thermometer
                        Prediction of riboswitch and RNA thermometer.
    crispr              Prediction of CRISPR.
    merge_features      Merge all features to one gff file.
    screenshot          Generate screenshot for selected feature.

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

License

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

Contact

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