SOAPindel

SOAPindel detects insertions and deletions (indels) in re-sequencing genomic data to identify homozygous, heterozygous, and complex variants.

Key Features:

• Indel detection: Identifies insertions and deletions in genomic sequences from re-sequencing data.
• Unmapped read assignment: Assigns unmapped reads to expected genomic positions using paired-end information.
• Paired-end support: Leverages paired-end reads to locate regions affected by indels that disrupt mapping.
• Local de novo assembly: Performs de novo assembly in regions with high numbers of unmapped reads.
• de Bruijn graph traversal: Uses exhaustive traversal of the de Bruijn graph during assembly to resolve variant sequences.
• Variant types resolved: Resolves homozygous, heterozygous, and complex indels.
• Output format: Produces a list of candidate indels with associated quality scores.
• Short indel performance: Demonstrates similar or superior detection performance for short indels (<10 base pairs) on simulated data.
• Long indel performance: Provides enhanced sensitivity and specificity for detecting long indels compared to some other methods.
• False-positive rate: Reported false-positive rate of approximately 10% for long indels exceeding 5 base pairs.
• Benchmarking: Evaluated in comparative analyses against Dindel, Pindel, and GATK on simulated data.
• Discovery yield: Identifies a greater number of candidate indels relative to other approaches in reported evaluations.

Scientific Applications:

• Indel discovery in re-sequencing projects: Detects insertions and deletions from re-sequencing datasets using paired-end reads and local assembly.
• Short and long indel characterization: Enables analysis of both short (<10 bp) and long indels, including sensitivity and specificity assessments.
• Genotype resolution: Facilitates identification of homozygous, heterozygous, and complex variant events.
• Method benchmarking: Serves as a comparator in performance evaluations against callers such as Dindel, Pindel, and GATK using simulated data.

Methodology:

SOAPindel assigns unmapped reads to expected positions via paired-end information, performs local de novo assembly in regions with many unmapped reads, exhaustively traverses the de Bruijn graph to resolve variants, and outputs candidate indels with quality scores.