SOAPsplice

SOAPsplice detects genome-wide splice junction sites and identifies alternative splicing (AS) events from RNA-Seq reads using next-generation sequencing data without relying on known splice junction annotations.

Key Features:

• Two-Step Approach: Performs ab initio splice junction detection using a two-step strategy of candidate identification followed by false-positive filtering.
• Candidate Identification: Identifies a broad set of potential splice junction candidates directly from RNA-Seq reads.
• False Positive Filtering: Applies two filtering strategies to substantially reduce false positives among candidate junctions.
• Performance Across Sequencing Depths: Maintains a low false positive rate and reliable junction detection in both simulated and real datasets, including at lower sequencing depths.
• Independence from Known Splice Junctions: Operates without requiring prior annotations of known splice junctions, enabling novel junction discovery.
• Alignment Independence: Employs an alignment-independent approach noted in benchmarking comparisons with splice-aware aligners.

Scientific Applications:

• Alternative Splicing Analysis: Detects and characterizes alternative splicing (AS) events across transcriptomes using RNA-Seq data.
• Splice Junction Discovery: Enables genome-wide discovery of splice junction sites in complex genomes and species with limited annotation.
• Transcriptome-wide Ab Initio Analysis: Facilitates ab initio transcriptome analysis from next-generation sequencing reads without relying on known junction databases.

Methodology:

Performs ab initio detection of splice junctions from RNA-Seq reads via a two-step pipeline: identification of candidate junctions followed by two filtering strategies to remove false positives, implemented with an alignment-independent approach.