TSSV

TSSV profiles targeted short structural variants, particularly short tandem repeats (STRs), by using two short flanking sequences to detect and characterize allelic STR structures in sequencing data.

Key Features:

• Targeted characterization: Performs targeted characterization of structural variation with a focus on short tandem repeats (STRs) and can be adapted to user-specified markers.
• Minimal sequence requirements: Operates using only two short flanking sequences, enabling analysis of highly polymorphic, repetitive, or uncharacterized loci without a full reference genome.
• High sensitivity and accuracy: Accurately determines allelic STR structures within complex mixtures and detects minor alleles down to ~10% representation, including cases where multiple samples share an STR allele.
• Demonstrated experimental use: Applied to characterize de novo mutations introduced by transcription activator-like effector nucleases (TALENs) and to profile noise and systematic errors in IonTorrent sequencing experiments.
• Complementary profiling: Provides high-resolution allelic profiles that complement other genomic analysis tools for the study of complex genomic regions.

Scientific Applications:

• TALEN mutation characterization: Characterizing de novo mutations introduced by transcription activator-like effector nucleases (TALENs).
• Sequencing error profiling: Profiling noise and systematic errors in IonTorrent sequencing experiments.
• Personal genomics: Generating high-resolution allelic profiles for individual genomic analyses involving STR variation.
• Forensic analysis: Resolving STR alleles for forensic genotyping and allele discrimination.
• Clinical diagnostics: Detecting and characterizing STR variants relevant to clinical diagnostic applications.

Methodology:

Utilizes two short flanking sequences to target specific loci and employs sensitive detection techniques to characterize allelic STR structures within complex mixtures, producing detailed profiles that complement other genomic analysis tools.