| name | bio-long-read-sequencing-isoseq-analysis |
| description | Discovers, classifies, filters, and quantifies full-length transcript isoforms from PacBio Iso-Seq/Kinnex (HiFi) and Oxford Nanopore (cDNA/direct-RNA) long reads, using the isoseq+pigeon pipeline, SQANTI3, and ONT tools (IsoQuant, FLAIR, Bambu, StringTie2). Covers why a novel isoform is an artifact until proven otherwise (RT template-switching, intra-priming, and 5' degradation manufacture junctions and truncations), the SQANTI3 structural categories and their trust order, the Kinnex skera-split step, orthogonal CAGE/poly-A/short-read-junction validation, and why long-read isoform quantification needs EM. Use when building a full-length isoform catalog, classifying/filtering long-read transcripts, running Iso-Seq or ONT cDNA/dRNA analysis, or judging novel-isoform reliability. |
| goal_approach_exempt | true |
| origin | openai4s |
| category | bioskills/long-read-sequencing |
| metadata | {"tool_type":"mixed","primary_tool":"SQANTI3","third_party":{"name":"GPTomics/bioSkills","repository":"https://github.com/GPTomics/bioSkills","commit":"d91ed3d563019e649dc854c56ccd62551359488a","license":"MIT"}} |
Version Compatibility
Reference examples tested with: isoseq 4.3+, pigeon 1.2+, SQANTI3 5.2+, pbmm2 1.13+, minimap2 2.28+, IsoQuant 3.4+.
Before using code patterns, verify installed versions match. If versions differ:
- CLI:
<tool> --version then <tool> --help to confirm flags
- Python/R:
pip show <pkg> / packageVersion('<pkg>') for SQANTI3/IsoQuant/Bambu
Results depend on inputs that outlive the binary version - record them:
- The reference annotation + genome version drive SQANTI3/pigeon classification; record them.
- Orthogonal support files (CAGE refTSS BED, poly-A motif/atlas, short-read STAR SJ.out) determine which novels survive; record their provenance.
- The Iso-Seq binary was renamed
isoseq3 -> isoseq in v4; the classifier pigeon is a separate binary.
If code throws an error, introspect the installed tool (isoseq --help, pigeon --help, sqanti3_qc.py --help) and adapt the example to the actual API rather than retrying.
Full-Length Isoform Analysis
"Find the isoforms in my long-read RNA data" -> Build a full-length isoform catalog, then classify and filter it against the reference with orthogonal end/junction support - because discovery without curation is a catalog of artifacts.
- CLI:
isoseq refine ... && isoseq collapse ... && pigeon classify ... && pigeon filter ... (PacBio), IsoQuant/FLAIR/Bambu (ONT)
The Single Most Important Modern Insight -- A Novel Isoform Is an Artifact Until Proven Otherwise
RT template-switching, intra-priming on genomic poly-A, and 5' RNA degradation actively MANUFACTURE novel junctions and truncated isoforms. So the classification + filter + orthogonal validation IS the analysis, not a QC postscript. Invert the posture from "I discovered N novel isoforms" to "I curated N novel isoforms that survived artifact filtering." Three consequences:
- A high novel-isoform fraction is a RED FLAG, not a success - it usually means an under-powered filter or degraded RNA, not unusually rich biology.
- ISM (incomplete-splice-match) is the RNA-degradation thermometer, not a discovery. ISMs are 5'-truncated FSMs; a high ISM fraction signals bad RNA integrity. Do not report ISMs as novel isoforms without CAGE 5' support.
- The orthogonal validation triad is mandatory: CAGE peaks for the 5' TSS (catches 5' degradation), poly-A atlas/motif for the 3' TES (catches intra-priming), and short-read STAR junctions for splice sites (catches RT-switch/NNC junk).
