Solas

Solas predicts and quantifies alternative transcript isoforms from exon-level RNA-Seq expression to analyze alternative splicing, polyadenylation, and differential promoter usage.

Key Features:

• Implementation: Provided as an R package for analysis of RNA-Seq exon-level data.
• Prediction and quantification: Uses an explicit statistical model to predict alternative isoforms and quantify their relative abundances from exon expression data.
• Condition comparison: Can perform isoform prediction and quantification within or between experimental conditions using any available gene annotation.
• Relative transcript quantification: Facilitates relative quantification of known transcript structures to assess isoform-level regulation.
• Input data: Integrates exon-level expression measurements from RNA-Seq with gene annotation data as primary inputs.
• Validation and correlation: Predictions have been validated by RT-PCR on human RNA-Seq datasets and show significant correlation with junction reads.
• Benchmarking: Demonstrates superior performance versus exon arrays for predicting skipped exons.

Scientific Applications:

• Mammalian transcriptome analysis: Dissects transcript isoform diversity and dynamic regulation in mammalian systems.
• Alternative splicing studies: Identifies and quantifies alternative splicing events including skipped exons.
• Polyadenylation and promoter usage: Analyzes alternative polyadenylation and differential promoter usage contributing to isoform diversity.
• Temporal and spatial expression profiling: Enables exploration of temporal and spatial patterns of isoform expression across biological contexts.
• Physiological and pathological investigations: Supports studies of isoform-level roles in physiological processes and disease states.

Methodology:

Integration of exon-level RNA-Seq expression with known gene annotations followed by application of an explicit statistical model to predict and quantify alternative transcript isoforms within or between experimental conditions.