IsoTools

IsoTools analyzes long-read transcriptome sequencing (LRTS) data in Python to identify and characterize alternative and differential splicing events.

Key Features:

• Comprehensive Data Structure: Integrates genomic information from LRTS transcripts with reference annotations in a unified data structure for downstream analysis.
• Quality Control and Visualization: Provides functions for quality control and visualization of LRTS-derived transcriptome data.
• Graph-Based Methodology: Implements a graph-based method to identify alternative splicing events and represent transcriptome complexity.
• Statistical Analysis: Employs a beta binomial distribution–based statistical approach to detect differential splicing events.

Scientific Applications:

• Alternative and Differential Splicing Analysis: Detects and characterizes alternative and differential splicing using long-read transcriptome sequencing data.
• Detection of Complex Novel Splicing Events: Leverages LRTS to reveal complex novel splicing events that can be missed by short-read RNA-Seq.
• PacBio Iso-Seq Case Study: Demonstrated on PacBio Iso-Seq data from human hepatocytes treated with valproic acid, an HDAC inhibitor, to detect transcriptional and splicing changes.

Methodology:

Implemented in Python; integrates genomic LRTS transcript information with reference annotations in a comprehensive data structure, applies a graph-based method to identify alternative splicing events, and uses beta binomial distribution–based statistical tests to detect differential splicing.