LESSeq

LESSeq identifies and quantifies alternative splicing events from short-read RNA-Seq data to enable discovery of differential splicing across conditions and species.

Key Features:

• Local event-based analysis: Focuses on local splicing events—specific regions within genes where transcript-splicing patterns diverge—to identify unambiguous alternative splicing events from short-read RNA-Seq.
• Quantification and significance testing: Uses Maximum Likelihood Estimation (MLE) to quantify the abundance of alternative splicing events and performs statistical significance testing across conditions.
• Short-read sequencing compatibility: Addresses challenges of inferring alternative splicing signatures from short-read sequencing technologies by concentrating on partial transcript structures.
• Implementation: Implemented in C++ and R for computational processing of RNA-Seq data.

Scientific Applications:

• Within-species differential splicing: Analysis of lymphoblastoid cell lines from two human populations to uncover population-differential alternative splicing events.
• Cross-species lineage-differential splicing: Comparison of human and rhesus macaque tissue RNA-Seq datasets to identify lineage-differential alternative splicing events.
• Evolutionary and functional studies: Investigation of cellular development, genetic variation, and evolutionary biology through detection of differential alternative splicing.

Methodology:

Analyzes short-read RNA-Seq by focusing on local splicing events and applies Maximum Likelihood Estimation for quantification and statistical significance testing.