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Research Interest

1. Theoretical population genetics

We develop mathematical models using coalescent theory, random processes, etc., to model the evolutionary dynamics of genetic variation of species and populations, including the allele frequency spectrum and haplotype structure. We also constructing computationally efficient statistical methods for analyzing genomic data, to infer population history and identify sites under natural selection

The methods we have developed: XP-CLR, IS-Age, HMM_Sweep, TNSFS, AFS-CH.


2. Comparative Genomics

We developed a method HDMKPRF to analyze population genomic data from multiple species; it can identify natural selection that occurs on a specific branch of the species tree, and effectively estimate the posterior distribution of the selection effect size of each gene.

Developed method:HDMKPRF


3. Evolutionary mechanism of complex phenotypes and quantitative traits

One long-term goal of the lab is to understand the genetics and evolution of complex phenotypes by analyzing genomic and phenotype data. The phenotypes we are currently working on include facial features, physical anthropological phenotypes, metabolic phenotypes of modern people, quantitative traits of crops, morphological phenotypes of domestic animals etc.


4. Forensic Genetics

We develop multiple methods for forensic genetics, such as, Y2Surname: inferring the surname of an unknown individual using the DNA profile from remains; AIM-SNPTag: constructing a highly informative AIM panels from genomic data; STRSensor: STR genotyping using next-generation sequencing data.

Developed methods:AIM-SNPTag, Y2Surname, STRsensor


5. Cancer microevolution and virus evolution

We develop population genetic methods to study tumor subcolonal evolution. Recently we also investigated the SARS-CV-2 genomes to understand whether the transmissibility and pathogenicity of SARS-CoV-2 in humans after zoonotic transfer is actively evolving, and driven by adaptation to the new host and environments.

 

 

 


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