HapKled

HapKled detects structural variants from Oxford Nanopore Technologies long-read alignment data by utilizing haplotype information to improve detection performance.

Key Features:

• Haplotype-tagging integration: HapKled conducts haplotype-tagging using Whatshap on reads to utilize haplotype information underlying alignment data.
• Haplotype-aware clustering: The tool alters clustering conditions according to haplotype information of signatures.
• Haplotype-based SV similarity determination: HapKled determines similar SVs based on haplotype information.
• Haplotype quality filtering: The tool applies slack filtering conditions based on haplotype quality.

Scientific Applications:

• Structural variant detection in genetic analysis: HapKled enables accurate detection of structural variants that influence phenotypes and cause diseases.
• Bioinformatics research: HapKled delivers improved SV detection results for research applications.
• Clinical diagnosis: HapKled could be useful in clinical diagnostic settings requiring accurate SV calling.
• Medical research and development: HapKled supports medical research through improved structural variant detection performance.

Methodology:

HapKled performs haplotype-tagging using Whatshap on Oxford Nanopore Technologies long-read alignment data, then applies three calling mechanics: altering clustering conditions according to haplotype information of signatures, determining similar SVs based on haplotype information, and applying slack filtering conditions based on haplotype quality.