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4.6 Gene-level analysis

Function

Gene-level analysis summarizes Ribo-seq or RNA-seq density at transcript and gene scale. These modules quantify CDS-level abundance, detect in-gene reading-frame switches, and draw IGV-like density profiles for genes of interest.

Submodules

Section Command Description
4.6.1 Gene quantification rpf_Quant Summarize RPF counts, RPM, RPKM, and TPM for CDS and optional UTR regions.
4.6.2 Frameshift detection rpf_Shift Detect in-gene reading-frame switches (programmed ribosomal frameshifts) from the merged density file.
4.6.3 Gene density plot rpf_Geneplot Draw IGV-like transcript/genome-coordinate density profiles for genes of interest.
  1. Run rpf_Quant after density merging to obtain gene-level abundance matrices.
  2. Run rpf_Shift to detect potential programmed ribosomal frameshifts or frame-switching artifacts in candidate transcripts.
  3. Run rpf_Geneplot to visually inspect the RPF density, frame composition, and coverage of candidate genes.

Input relationship

Most commands in this section use the merged density table generated by rpf_Merge, usually named RIBO_merged.txt or RNA_merged.txt. rpf_Shift additionally requires a frame-resolved density file, so it should be run on the *_rpf_merged.jsonl.gz output of rpf_Merge. rpf_Geneplot reads the same merged file and accepts both the compact JSONL and the plain TXT table.

Notes

  • For standard translation-level quantification, use CDS density and trim codons near the start and stop codons to reduce initiation and termination artifacts.
  • Gene-level metrics are useful for expression overview, replicate quality control, and downstream differential analysis, but they should be interpreted together with read periodicity, metagene profiles, and coverage uniformity.
  • Frameshift candidates from rpf_Shift are statistical detections: always validate the shift site and direction manually (e.g. with the per-candidate gene plots) before reporting biological conclusions. rpf_Geneplot is the general-purpose tool for visually inspecting the density of any gene of interest.