rSeqNP

rSeqNP detects differential gene expression and alternative splicing using a non-parametric permutation-based framework.

Key Features:

• Non-Parametric Statistical Model: Analyzes transcriptomic data without assuming predefined data distributions, enabling application across diverse experimental designs.
• Permutation-Based Isoform Integration: Uses permutation tests and integrates multiple isoforms to identify differentially expressed and alternatively spliced genes.

Scientific Applications:

• Transcriptomic Differential Analysis: Identifies gene expression changes and alternative splicing events across conditions, tissues, or developmental stages.

Methodology:

rSeqNP applies a non-parametric framework based on permutation testing to evaluate statistical significance of expression and splicing differences, integrating isoform-level information to detect regulated genes.