WEScall

WEScall performs genotype calling for whole exome sequencing (WES) data by integrating target and off-target reads to improve genotyping accuracy and enable downstream association and risk-prediction analyses.

Key Features:

• Integration of target and off-target data: Utilizes linkage disequilibrium (LD) shared within study samples and an external reference panel to analyze both target and off-target WES sequences.
• Improved genotyping accuracy: In a study of 2,527 individuals of Chinese and Malay descent across ~1.1 million SNPs in deeply sequenced target regions, reduced genotype discordance from 0.26% (standard error 6.4×10^-6) to 0.08% (standard error 3.6×10^-6), and achieved 0.70% discordance (standard error 3.0×10^-6) for off-target SNPs with average sequencing depth ~1.2 times higher than typical.
• Application in genome-wide association studies (GWAS): Enabled identification of 10 loci associated with metabolic traits at genome-wide significance (P<5×10^-8), including eight known loci and two novel associations GPATCH8-SLC4A1 (rs369762319, P=2.56×10^-12) and ROR2 (rs1201042, P=3.24×10^-8) linked to glycated haemoglobin.
• Enhancement of polygenic risk prediction: Incorporation of off-target data improved polygenic risk prediction using summary statistics from the UK Biobank and Biobank Japan, with six of nine traits showing significant improvement (P<0.01).

Scientific Applications:

• Variant discovery and genotyping in WES studies: Enables more accurate genotype calls across coding and adjacent non-coding regions by leveraging off-target reads.
• Genome-wide association studies (GWAS): Supports GWAS including discovery of loci associated with metabolic traits, demonstrated by identification of 10 significant loci and two novel associations for glycated haemoglobin.
• Polygenic risk prediction: Improves polygenic score performance by increasing genotype accuracy and variant recovery when using external summary statistics from cohorts such as UK Biobank and Biobank Japan.

Methodology:

Implements a genotype calling pipeline that integrates linkage disequilibrium information from within the study cohort and an external reference panel to leverage off-target WES data.