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differential-splicing

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Detects differential alternative splicing between conditions using rMATS-turbo (binomial LRT on junction counts), leafcutter (Dirichlet-multinomial GLM on intron clusters), MAJIQ V3 deltapsi/HET (Bayesian posterior on LSVs), SUPPA2 (empirical-null on TPM-derived PSI), or Shiba (junction-imbalance-corrected, 2025 SOTA at low coverage). Reports FDR-corrected significance and delta PSI effect sizes. Tools differ in statistical model, annotation dependence, calibration regime, and replicate-count requirements. Use when comparing splicing patterns between treatment groups, tissues, or disease states.

When to use

• comparing splicing patterns between treatment groups
• comparing splicing patterns between tissues
• comparing splicing patterns between disease states
• standard n=3 vs n=3 designs
• small pilot n=2 vs n=2 designs
• heterogeneous cohort designs
• paired tumor-normal designs
• non-model organism without annotation

When not to use

• single-sample-vs-cohort outlier detection
• time-course / multi-condition design
• long-read splicing analysis

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