Quan Long

The paper introduces a model-free permutation method to estimate P-values in genetic studies, reducing computational demands while maintaining accuracy.

MOKA integrates multi-omics data into GWAS using a kernel association test pipeline, identifying 89 significant genes in schizophrenia with 15.7% validation in DisGeNET.

This study integrates large-scale omics and electronic health records to identify risk proteins and drugs for cancer prevention, finding 101 novel proteins and three drugs associated with reduced colorectal cancer risk.

Apollo simulates within-host viral evolution and infection dynamics, validating limitations of transmission inference tools using HIV cohort data.

The paper introduces AE-TWAS, a method that improves genotype-phenotype association studies by transforming transcriptome data with autoencoders to enhance expression heritability and TWAS performance.

This study introduces transTF-TWAS, a method that integrates transcription factor-linked trans-located variants into transcriptome-wide association analyses to improve disease risk gene discovery.

This paper introduces edLMM, a method that detects low-effect genetic variants using moderate sample sizes, improving missing heritability estimation.

IMAS, a statistical method, uses image-derived phenotypes from the UK Biobank to discover genetic associations with four brain disorders, revealing a common cerebellar mechanism.

This study identifies and corrects cross-validation bias in genomic prediction methods using CVc, showing effectiveness for most methods except Lasso and ENET.

The paper applies transfer learning to adapt a general-purpose model to a specific domain using limited data, demonstrating improved performance in breast cancer-related tasks.

This paper shows that re-implementing a traditional linear mixed model with a modern gradient solver can outperform deep learning models in speed and accuracy for biological data.

CATE accelerates evolutionary genomic tests using GPU and CPU parallelization, achieving over 180x speedup compared to standard tools.

This study identifies nkx3.1-expressing precursors in zebrafish that differentiate into brain pericytes and shows their regulation by cxcl12b-Cxcr4 signaling.

This paper shows that combining feature selection and aggregation in GReX limits TWAS power and adaptability, especially with low expression heritability.

WgLink improves whole-genome viral haplotype reconstruction accuracy and reduces memory usage by integrating local reconstructions with L0+L1 regularization.

kTWAS combines TWAS feature selection with SKAT kernel methods to improve statistical power and identify novel disease-associated genes.

The paper introduces ILMM, a statistical model that integrates genetic interactions into genotype-phenotype association mapping, revealing 3D-genetic basis of ASD and 3D-eQTLs using whole genome and transcriptome sequencing data.

This paper compares the power of GWAS, TWAS, and a hypothetical real expression protocol to determine when TWAS is effective and when GWAS is better.

PoolHapX reconstructs microbial haplotypes by integrating genetic sharing and genomic sequencing, outperforming existing tools and revealing new insights into HIV evolution.