Xiaolei Liu

The paper introduces PIXANT, a multi-phenotype imputation method that improves GWAS power by imputing 425 phenotypes for 277,301 individuals, leading to the discovery of 18.4% more GWAS loci.

hibayes provides an R package for fitting Bayesian regression models in genomic prediction and GWAS, supporting individual-level, summary-level, and single-step approaches.

SEIR is a multi-locus GWAS method that improves statistical power for identifying variant-phenotype associations by integrating an embedded selector with iterative single-marker scanning.

This paper develops a CRISPR/Cas12a-based colorimetric assay with a convolutional neural network for rapid, naked-eye detection of viral nucleic acids in point-of-care testing.

rMVP improves GWAS computation by offering memory efficiency, visualization tools, and parallel acceleration for faster and more scalable analysis.

This study uses UAV-based phenotyping to analyze plant height in maize across four growth stages, identifying 238 QTLs associated with plant height traits.

BLINK improves statistical power and reduces computing time for GWAS by replacing FarmCPU's bin method with Bayesian information criteria and linkage disequilibrium information.