SplicingFactory

SplicingFactory computes transcript-level RNA isoform diversity from RNA-seq quantifications in R using metrics such as Shannon entropy and the Gini index to quantify and compare alternative splicing across samples and conditions.

Key Features:

• Isoform Diversity Metrics: Calculates multiple RNA isoform diversity metrics from transcript-level expression values to characterize isoform distributions.
• Statistical Analysis: Implements Shannon entropy and the Gini index to quantify transcript isoform diversity.
• Comparative Analysis: Detects significant changes in isoform diversity between samples or biological conditions, including effects of mutations, drug treatments, or environmental differences.
• Application to Disease Research: Applied to CD34+ hematopoietic stem cells and myelodysplastic syndrome samples to identify genes with altered isoform diversity associated with SF3B1 mutations.
• Integration with RNA-seq Data: Evaluates the impact of RNA-seq quantification tools, quantification uncertainty, gene expression levels, and number of isoforms on diversity calculations.
• R package implementation: Provided as an R package for analysis of transcript-level expression data.

Scientific Applications:

• Alternative splicing research: Quantifies isoform diversity to study alternative splicing within and between biological samples.
• Disease mechanism studies: Investigates disease-related changes in isoform diversity, exemplified by analyses of SF3B1-mutant myelodysplastic syndrome.
• Technical assessment: Assesses how RNA-seq quantification tools and quantification uncertainty influence diversity estimates.
• Target identification: Supports identification of genes with altered isoform diversity that may inform molecular underpinnings of diseases and potential therapeutic targets.

Methodology:

Calculates diversity metrics (including Shannon entropy and the Gini index) from transcript-level expression values and analyzes them to detect significant changes between conditions while evaluating the effects of RNA-seq quantification tools, quantification uncertainty, gene expression levels, and number of isoforms on diversity calculations.