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1 Overview

RiboParser is designed for complete RNA-seq and ribosome profiling data analysis. This page only provides the conceptual overview; detailed commands are placed in the workflow pages to avoid duplication.

What RiboParser does

The complete workflow consists of two parts: a public pipeline that can be handled by general bioinformatics tools, and the RiboParser-specific analysis described below.

Public pipeline (general tools):

  • reference preparation for transcriptome-aware Ribo-seq analysis
  • RNA-seq and Ribo-seq raw data cleaning
  • contaminant classification against rRNA, tRNA, ncRNA, mRNA, and genome indexes
  • splice-aware genome alignment
  • transcriptome quantification

RiboParser-specific analysis:

  • Ribo-seq quality control
  • P-site offset inference
  • RNA/Ribo read density construction
  • merged density matrix generation
  • periodicity, metaplot, coverage, and correlation analysis
  • gene-level quantification and read-density retrieval
  • codon-level pausing, occupancy, decoding time, selection time, variation, and odds-ratio analysis
  • smORF scanning, clustering, Ribo-seq evidence evaluation, and quantification
  • SeRP signal and peak analysis
  • helper utilities for FASTA, FASTQ, bedGraph, Bowtie logs, RSEM tables, and merged Ribo-seq outputs

Citation

Ren, S., Li, Y. & Zhou, Z.
RiboParser/RiboShiny: An integrated platform for comprehensive analysis and visualization of ribo-seq data.
Journal of Genetics and Genomics (2025).
doi:10.1016/j.jgg.2025.04.010.