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维护者 FreedomIntelligence · 最近更新 2026年4月1日
Detects differential alternative splicing between conditions using rMATS-turbo (BAM-based) or SUPPA2 diffSplice (TPM-based). Reports events with FDR-corrected significance and delta PSI effect sizes. Use when comparing splicing patterns between treatment groups, tissues, or disease states.
原始来源
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-differential-splicing
技能摘要
原始文档
| Tool | Input | Approach | Strengths |
|---|---|---|---|
| rMATS-turbo | BAM | Junction counting | Novel junctions, statistical model |
| SUPPA2 | TPM | Transcript ratios | Speed, isoform-aware |
| leafcutter | BAM | Intron clustering | Novel events, no annotation bias |
Goal: Detect statistically significant differential splicing events between two conditions from BAM files.
Approach: Run rMATS-turbo on condition-grouped BAMs, then filter results by FDR and delta PSI thresholds.
"Find differential splicing between conditions" -> Compare junction-level inclusion across sample groups with statistical testing.
rmats.py + pandas filtering (rMATS-turbo)suppa.py diffSplice (SUPPA2, TPM-based)leafcutter_ds.R (leafcutter, annotation-free)
## Load results for skipped exons
se = pd.read_csv('rmats_output/SE.MATS.JC.txt', sep='\t')
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