Zilin Li

MetaSTAARlite is a tool for rare variant meta-analysis using summary statistics from biobank-scale whole-genome sequencing data, showing linear scaling and concordance with pooled analysis.

The paper maps rare coding and noncoding variants to 1,342 diseases and biomarkers using whole genome sequencing data from 490,549 UK Biobank participants.

cellSTAAR integrates single-cell ATAC-seq with whole-genome sequencing to enhance power and interpretation of rare variant association tests in non-coding regions.

The paper introduces vcf2agds, a toolkit converting WGS data to aGDS format, enabling efficient analysis of UK Biobank data and identifying 480 genome-wide significant associations for total cholesterol.

The paper identifies 83 rare lncRNA variant sets associated with blood lipid levels using WGS data from the TOPMed program and validates some in UK Biobank data.

The paper analyzes inflammation biomarkers using whole-genome sequencing from the TOPMed consortium, identifying both single-variant and rare variant associations with inflammatory traits.

The paper introduces a framework for detecting noncoding rare variant associations using whole-genome sequencing data, applying it to lipid traits in the TOPMed program.

FAVOR provides an online resource and tool for functional annotation of variants from whole genome sequencing studies to aid in disease gene prioritization.

The paper performs whole genome sequence analysis of plasma lipid levels in 66,329 individuals, identifying new lipid-associated alleles, including rare non-coding variants.

The paper introduces a cloud-based workflow for rare variant analysis in whole genome sequencing studies, enabling scalable and reproducible analysis with functional annotations.

The paper estimates heritability for height and BMI using whole-genome sequence data and finds that rare variants contribute significantly to the missing heritability.

The paper introduces MACIE, a framework for predicting functional variants by integrating diverse annotations, and applies it to fine-mapping using GWAS data.

APEX is a toolkit for molecular QTL mapping and meta-analysis that improves scalability and accuracy for large datasets and summary statistics.

The paper identifies two EBV variants in BALF2 associated with increased NPC risk through genome sequencing and association studies in China.

The paper introduces SCANG, a dynamic scan statistic method for detecting rare-variant association regions in WGS data without pre-specifying window sizes, showing improved performance over existing methods.

ACAT improves power for rare-variant analysis by combining p-values using two tests, ACAT-V and ACAT-O, showing robustness and higher power than existing methods.

The paper introduces SMMAT, a variant-set mixed model association test for continuous and binary traits in large-scale WGS studies, showing it controls type I error rates and applies to population structured and related samples.