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8 Acknowledgements

RiboParser/RiboShiny was developed to provide an integrated platform for comprehensive analysis and visualization of ribosome profiling data.

Software ecosystem

RiboParser depends on and interoperates with widely used open-source tools, including:

  • Bowtie
  • SAMtools
  • Cutadapt
  • STAR
  • BEDTools
  • Subread
  • RSEM
  • gffread
  • SRA Toolkit
  • UCSC utilities
  • NumPy
  • pandas
  • Polars
  • Biopython
  • SciPy
  • scikit-learn
  • statsmodels
  • pysam
  • joblib
  • matplotlib
  • matplotlib-venn
  • seaborn

Example dataset

The documentation uses public RNA-seq and Ribo-seq datasets to demonstrate the workflow.

Nedialkova DD, Leidel SA.
Optimization of Codon Translation Rates via tRNA Modifications Maintains Proteome Integrity.
Cell 2015 Jun 18;161(7):1606-18.
PMID: 26052047

Community

We thank all developers, users, and researchers who provide feedback, report issues, test RiboParser on different species and sequencing datasets, and contribute to the improvement of RiboParser and RiboShiny.