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bulkrna-splicing

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Load when summarising rMATS / SUPPA2 alternative-splicing output and identifying significant differential splicing events. Skip if you only have count-level DE (use bulkrna-de) or for splicing in single-cell or spatial data (currently unsupported).

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How to use this skill

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Source SKILL.md: https://github.com/TianGzlab/OmicsClaw/blob/HEAD/skills/bulkrna/bulkrna-splicing/SKILL.md

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bulkrna-splicing

When to use

Run AFTER rMATS or SUPPA2 has produced its splicing-event table — this skill consumes that output (not raw alignments). Computes per-event ΔPSI (delta percent-spliced-in), flags events crossing significance and ΔPSI thresholds, and groups results by event type (SE / A3SS / A5SS / MXE / RI).

Inputs & Outputs

InputFormatRequired
Splicing event table.csv from rMATS or SUPPA2 (event_id, type, ΔPSI, p-value cols)yes (or --demo)
--dpsi-cutofffloatdefault 0.1 (events with abs ΔPSI ≥ this)
--padj-cutofffloatdefault 0.05 (significance threshold)
OutputPathNotes
All eventstables/splicing_events.csvfull annotated event table
Significant eventstables/significant_events.csvfiltered by --dpsi-cutoff and --padj-cutoff
ΔPSI distributionfigures/dpsi_distribution.pnghistogram with cutoff lines
Event-type breakdownfigures/event_type_distribution.pngSE / A3SS / A5SS / MXE / RI counts
Volcanofigures/volcano_splicing.pngΔPSI vs -log10(padj)
Reportreport.md + result.jsonalways

Flow

  1. Load splicing event table. Hard-fail at bulkrna_splicing.py:365,368 on missing or invalid --input.
  2. Validate the fixed input schema: must contain columns event_type, gene, delta_psi, padj (bulkrna_splicing.py:153-155). No format detection — caller must pre-flatten rMATS / SUPPA2 output to this schema.
  3. Filter by --dpsi-cutoff AND --padj-cutoff.
  4. Group by event type; render distribution + volcano + bar plots.
  5. Emit tables/splicing_events.csv (full) + tables/significant_events.csv (filtered) + report.

Gotchas

  • This skill consumes the SPLICING TABLE, not BAM or FASTQ. Run rMATS or SUPPA2 upstream and feed their output here. The wrapper does not perform splicing detection itself — feeding it BAM files raises a parser error or silently produces an empty result.
  • --dpsi-cutoff is the ABSOLUTE value of ΔPSI. Default 0.1 keeps events with |ΔPSI| ≥ 0.1, including both inclusion-up and inclusion-down. Set to 0 to keep all directionally significant events.
  • Input schema is fixed: event_type, gene, delta_psi, padj (with optional pvalue and event_id). The script does NOT auto-detect rMATS vs SUPPA2 column conventions — if your input uses rMATS's IncLevelDifference/FDR or SUPPA2's dPSI/pval natively, rename columns first or the loader will silently drop your data.
  • Event-type breakdown depends on the upstream tool's classification. rMATS reports SE / A3SS / A5SS / MXE / RI as separate files; SUPPA2 uses an EVENT field. Concatenate / re-label these into a single event_type column before feeding the skill, or the breakdown bar chart under-counts.

Key CLI

python omicsclaw.py run bulkrna-splicing --demo
python omicsclaw.py run bulkrna-splicing \
  --input rmats_se.csv --output results/
python omicsclaw.py run bulkrna-splicing \
  --input suppa2_events.csv --output results/ \
  --dpsi-cutoff 0.2 --padj-cutoff 0.01

See also

  • references/parameters.md — every CLI flag and tuning hint
  • references/methodology.md — rMATS vs SUPPA2 format conventions, event-type taxonomy
  • references/output_contract.md — exact output directory layout
  • Adjacent skills: bulkrna-de (parallel: gene-level DE, complements exon-level splicing), bulkrna-enrichment (downstream: pathway view of splicing-affected genes via gene-symbol mapping)