cirCodAn

cirCodAn (circular Coding sequence Annotator) is a computational tool designed to predict CDS in circRNAs.

• cirCodAn is an extension of CodAn, which was designed to predict CDS in linear RNAs.

Quick Installation

• Clone the cirCodAn repository:

  • git clone https://github.com/denilsonfbar/cirCodAn.git

• Add the cirCodAn and CodAn/bin folder into your PATH:

  • export PATH=$PATH:$PWD/cirCodAn/ && export PATH=$PATH:$PWD/cirCodAn/CodAn/bin/
  • to add cirCodAn permanently to your PATH, add the previous "export" commands into your ~/.bashrc or ~/.bashprofile

• Apply "execution permission" to executables if needed:

  • chmod +x $PWD/cirCodAn/*.py && chmod +x $PWD/cirCodAn/CodAn/bin/*

Requirements

• Python3, Biopython, and Pandas
  • apt-get install python3-biopython python3-pandas
• Perl, Bioperl and MCE
  • apt-get install bioperl libmce-perl
• CodAn
• ToPS

Ensure that all requirements are working properly.

⚠️ Conda environment installation

If you are not the root user and takes advantage of Conda (i.e., one of the famous environment management system), you can follow the steps below:

• Create the conda environment with all dependencies:

  • conda create -n circodan_env -c bioconda codan pandas
  • git clone https://github.com/denilsonfbar/cirCodAn.git
  • export PATH=$PATH:$PWD/cirCodAn/
    • to add it permanently to your PATH, add the command export PATH=$PATH:$PWD/cirCodAn/ into your ~/.bashrc or ~/.bashprofile
  • chmod +x $PWD/cirCodAn/*.py

• Activate the environment before use:

  • conda activate circodan_env

Usage

Usage: circodan.py [options]

Options:
  -h, --help            show this help message and exit
  -f file, --file=file  Mandatory - input circRNAs file (FASTA format),
                        /path/to/circRNA_seqs.fa
  -o folder, --output=folder
                        Optional - path to output folder,
                        /path/to/output/folder/ if not declared, it will be
                        created at the circRNAs input folder
                        [default="cirCodAn_output"]
  -m folder, --model=folder
                        Optional - path to model folder
                        [default="models/VERT_circ"]

Basic usage:

circodan.py -f circRNA_seqs.fa

Testing the installation

To test if cirCodAn is properly working, just run the testing set:

circodan.py -f example/circRNA_seqs.fa

Expected example output

2023-03-15 17:07:25 -> started cirCodAn v1.0
2023-03-15 17:07:26 -> prediction finished
Number of input sequences -> 138
Number of predicted CDSs  -> 104
GTF file with prediction annotation -> example/cirCodAn_output/CDS_predicted.gtf
Predicted CDS seqs FASTA file -> example/cirCodAn_output/CDS_predicted_seqs.fa
Predicted peptides FASTA file -> example/cirCodAn_output/CDS_predicted_seqs_aa.fa

Outputs

cirCodAn_output/
├── CDS_predicted_seqs.fa
├── CDS_predicted_seqs_aa.fa
└── CDS_predicted.gtf

This repository

• CodAn/: original CodAn files
• datasets/: datasets used in cirCodAn development and evaluation
• development/: raw data and scripts of cirCodAn development and evaluation
• example/: circRNA example file
• literature_search/: bibliometric analysis files
• models/: ToPS GHMM models for circRNA

Citation

If you use or discuss cirCodAn, please cite the following:

Barbosa, D. F., Oliveira, L. S., Nachtigall, P. G., Valentini Junior, R., Souza, N., Paschoal, A. R., Kashiwabara, A. Y. (2024). cirCodAn: A GHMM-based tool for accurate prediction of coding regions in circRNA. Advances in Protein Chemistry and Structural Biology, Academic Press. ISSN 1876-1623, https://doi.org/10.1016/bs.apcsb.2023.11.012.

Nachtigall, P. G., Kashiwabara, A. Y., & Durham, A. M. (2021). CodAn: Predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, 22(3), 1–11. https://doi.org/10.1093/bib/bbaa045

License

GNU GPLv3

Contact

To report bugs, to ask for help and to give any feedback, please contact [email protected]