Jonathon LeFaive

The paper introduces a phenotype-genotype reference map for replicating GWAS results in biobank data and demonstrates its utility in detecting data corruption and assessing reproducibility.

This paper provides a statistical genetics guide for imputing HLA alleles from genotype data and offers best practices for association testing to identify HLA variants driving complex diseases.

The paper introduces FixItFelix and a modified GRCh38 reference to improve variant calling and expression analysis in genes with reference errors, showing benefits across multiple sequencing types and populations.

This paper introduces RUTH, a new HWE test that accounts for population structure and genotype uncertainty, showing it reduces false positives compared to traditional methods.

Over 400 million variants, 97% below 1% frequency, emerge from deep whole-genome sequencing of 53,831 diverse TOPMed participants; TOPMed haplotypes enable imputation down to ~0.01% frequency.

SAIGE-GENE is a scalable generalized linear mixed model for region-based association tests in large cohorts, efficiently handling over 400,000 samples with controlled type I error rates.

This study constructs and evaluates polygenic risk scores for skin cancer subtypes using the Michigan Genomics Initiative and UK Biobank data, and develops a visual catalog to compare PRS methods.

The paper identifies loss-of-function variants affecting liver-related blood traits that reduce CVD risk without increasing metabolic disease risk, highlighting potential therapeutic targets.

This paper introduces SAIGE, a method that improves the accuracy of genetic association tests in unbalanced case-control studies by using saddlepoint approximation, and demonstrates its effectiveness on UK Biobank data.