Ribose-Map-QC

To get quality control of files generated by Ribose-Map. Also supported by percentage and composition of rNMPs from ribose-seq output

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Installation

Getting the code

The development version from GitHub with:

sh git clone https://github.com/DKundnani/Ribose-Map-QC.git

Creating the enviroment with required dependencies

sh conda env create --name RibosemapQC_env --file /Ribose-Map-QC/env.yml

Additional Dependencies

• Ribosemap generated output (For more info, see here: https://github.com/agombolay/ribose-map)
• Trimmed reads used in Ribosemap
• Reference genome of the organism being used (also used in Ribosemap)

Usage

Getting QC report

bash cd $outputdir #This would be the results directory generated by Ribose-Map. Please make sure you have generate alignment, coordinate and composition modules to get the results and the names to trimmed files match names of folders as output of Ribosemap. files will contain the library name as first column and sample name as second column(example present in repository. python3 path/to/Ribose-Map-QC/quality.py -f path/to/files -t path/to/trimmed_reads -r path/to/reference/sacCer2/sacCer2.fa #Generates QC.tsv as output

Getting counts using bed file

bash Place all the bed files in a folder e.g. path/to/bed generate_QC_frombed.py f path/to/files -r path/to/reference/sacCer2/sacCer2.fa #Generates QC.tsv as output

Visualization

bash conda activate RibosemapQC_env #activating Enviroment Rscript path/to/Ribose-Map-QC/qualviz.R -q QC.tsv -l files #Using QC.tsv generated from either quality.py or qual_short.py Rscript path/to/Ribose-Map-QC/counts_viz.R -c QC.tsv -l files #Using QC.tsv generated from generate_QC_frombed.py

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Deepali L. Kundnani - deepali.kundnani@gmail.com

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Citations

Use this space to list resources you find helpful and would like to give credit to. I've included a few of my favorites to kick things off!

• Distinct features of ribonucleotides within genomic DNA in Aicardi-Goutires syndrome (AGS)-ortholog mutants of Saccharomyces cerevisiae Deepali L. Kundnani, Taehwan Yang, Alli L. Gombolay, Kuntal Mukherjee, Gary Newnam, Chance Meers, Zeel H. Mehta, Celine Mouawad, Francesca Storici bioRxiv 2023.10.02.560505; doi: https://doi.org/10.1101/2023.10.02.560505
• Kundnani, D. (2024). Ribose-Map-QC (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.10455801

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