Computational genomics and genetics in livestock.
I am a computational genomics and genetics researcher interested in understanding how genomic variation contributes to phenotypic variation and economically important traits in livestock. My research focuses on comparative genomics, pangenomics, structural variation, and functional genomics, integrating long-read sequencing, phased genome assembly, pangenome graphs, and multi-omics approaches to characterize genome diversity and its functional consequences.
My work spans cattle, pigs, sheep, and goats, with a focus on translating genomic variation into biological and breeding insights. I have served as PI of an NSFC Youth Science Fund project and have published 37 peer-reviewed papers, including 15 as first, co-first, or corresponding author in journals including Nature Communications and Genome Biology.
Postdoctoral researcher in the Department of Animal and Avian Sciences at the University of Maryland, working jointly with the Animal Genomics and Improvement Laboratory at USDA-ARS in Beltsville.
| What it does | |
|---|---|
| cattleHolPanSV | HiFi assembly, Minigraph-Cactus pangenome construction, SV and SNV calling across long- and short-read platforms, cross-caller benchmarking, and SV-GWAS. Nature Communications, 2026 - 10.1038/s41467-026-68807-4 |
| cattlePanSVimp | Combined SV+SNP reference panels, imputation accuracy across four marker densities (LD chip, HD chip, WGS SNP, RNA SNP), and GWAS on the imputed panels. Nature Communications, 2026 - 10.1038/s41467-026-75219-x |
Both are code only. They were written for a Slurm cluster with Singularity, and reproducing either end to end needs the sequence data listed in its data-availability section plus substantial compute. The individual stages are readable and reusable on their own.
Genomics Pangenome analysis, structural variant and copy number variant discovery, GWAS, eQTL, A-to-I RNA editing, single-cell and spatial transcriptomics, alternative splicing, regulatory element annotation
Data types PacBio HiFi, Oxford Nanopore, whole-genome resequencing, RNA-seq, ATAC-seq, DNA methylation, multi-omics integration
Computing Linux and HPC, Python, R, Shell, Snakemake, Nextflow, Docker, Singularity/Apptainer, Git
Statistics and machine learning Quantitative genetic analysis in R and SAS, Bayesian inference, random forests and gradient boosting for complex trait prediction, deep learning applied to genomic discovery (DeepVariant, AlphaFold)
AI for research workflows Deploying and fine-tuning local large language models with Ollama for research automation, and GPU-accelerated bioinformatics on local hardware
- liuyang.oxggi.com - writing, publications, and what I work on
- ORCID 0000-0002-4179-8587 - Google Scholar - PubMed
I take on analysis projects: pipeline design, pangenome and graph assessment, variant genotyping, imputation, and association work. Details and contact are at liuyang.oxggi.com.
Views are my own, not those of UMD or USDA.