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4.8 smORF analysis

Function

The smORF analysis module provides a complete workflow for scanning candidate small open reading frames (smORFs), filtering and clustering candidates with sequence and Kozak-context criteria, evaluating Ribo-seq translation evidence, and quantifying P-site density for reliable smORFs.

The workflow is designed for transcript-centric smORF discovery. Candidate ORFs are first generated from a genome FASTA and genePred annotation, then filtered and evaluated using P-site density tracks from Ribo-seq data.

Workflow

smorf_scanner → smorf_cluster → smorf_evidence → smorf_quant
Step Command Main purpose
1 smorf_scanner Scan transcript-centric candidate ORFs from genome FASTA and genePred annotation.
2 smorf_cluster Filter scanned ORFs by sequence and Kozak-context criteria, then cluster them into non-redundant ORF families.
3 smorf_evidence Evaluate family-aware Ribo-seq translation evidence and classify reliable smORFs.
4 smorf_quant Quantify raw P-site density counts for reliable smORFs from per-sample density tracks.

Input overview

Input Used by Description
Genome FASTA smorf_scanner Genome sequence used to reconstruct transcript sequences.
genePred annotation smorf_scanner, optional for smorf_evidence Transcript annotation. Scanner uses it to define transcript structures; evidence uses it to recover ORF exon blocks when needed.
Scanner message table smorf_cluster Candidate ORF table generated by smorf_scanner.
Clustered ORF table smorf_evidence Clustered family table generated by smorf_cluster.
P-site density files smorf_evidence Strand-specific or unstranded bedGraph/WIG files containing Ribo-seq P-site density.
Reliable smORF genePred smorf_quant Reliable smORF genePred generated by smorf_evidence.
Density list smorf_quant Design table pointing to the per-sample P-site density tracks.

Main evidence levels

Evidence Meaning
ORF sequence Start codon, stop codon, ORF length, strand, and category.
Kozak context Start-codon context scored by annotated, built-in, PWM, or sequence-derived Kozak models.
Ribo-seq signal Total RPF signal, covered nucleotides/codons, and coverage ratio.
Periodicity Frame-specific signal distribution, especially frame-0 enrichment.
Start site Resolved start site, leading-window support, and noncanonical extension.
Coverage shape Uniform, disperse, or skewed RPF distribution across the ORF.
Multi-sample support Reproducibility and support level across multiple Ribo-seq samples.
Quantification Raw P-site density count matrix for reliable smORFs across samples.

Notes

  • smorf_scanner produces many candidate ORFs. Scanner output alone should not be treated as evidence of translation.
  • smorf_cluster filters and clusters candidates according to sequence features and Kozak context, but it does not use Ribo-seq evidence.
  • smorf_evidence requires a density list pointing to the P-site density tracks of every sample.
  • smorf_quant is most useful when multiple Ribo-seq samples or replicates are available.
  • Strand-specific P-site density files can be generated with rpf_Bam2bw and then supplied to smorf_evidence as bedGraph or WIG tracks.