Human Genetics   |   Computational Genomics   |   Immunogenomics

Human Genetics

Identify genetic causes of human diseases by integrative analysis of genetics variants with functional genomics rooted in biological mechanisms. To improve the ability to identify risk variants and genes, we develop new computational methods to integrate gene expression and epigenomic data with genetic data. These methods are usually based on machine learning models with heuristics developed from biological mechanisms, such as haploinsufficiency. We apply these methods in genetic studies of human diseases in collaboration with Dr. Wendy Chung's group. In the last few years, we have been focusing on developmental disorders, such as congenital diaphragmatic hernia, congenital heart disease, and autism.

Recent papers

  1. De novo variants in congenital diaphragmatic hernia identify MYRF as a new syndrome and reveal genetic overlaps with other developmental disorders

    Qi H*, Yu L*, Zhou X*, et al, (2018)
    PLOS Genetics

  2. SPARK: A US Cohort of 50,000 Families to Accelerate Autism Research

    SPARK Consortium & (2018)

  3. Exome Sequencing in Children With Pulmonary Arterial Hypertension Demonstrates Differences Compared With Adults

    Zhu N*, Gonzaga-Jauregui C*, Welch CL*, et al (2018)
    Circulation: Genomic and Precision Medicine

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Computational Genomics

Develop computational methods to identify and interpret genetic variations from genome sequencing data. Ongoing projects include detecting copy number variants and structural variants from exome or genome sequencing data, accurate estimation of genotype likelihood from sequencing data using deep learning, predicting genetic effect of missense or noncoding variants.

Recent papers

  1. MVP: predicting pathogenicity of missense variants by deep learning

    Qi H*, Chen C*, et al. (2018)

  2. Coverage Tradeoffs and Power Estimation in the Design of Whole-Genome Sequencing Experiments for Detecting Association

    Shen Y et al, (2011)

  3. A SNP discovery method to assess variant allele probability from next generation resequencing data

    Shen Y et al (2010) 
    Genome Research 

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Computational analysis and mathematical modeling to understand dynamics of immune cells in human.

Recent papers

  1. Human Tissue-Resident Memory T Cells Are Defined by Core Transcriptional and Functional Signatures in Lymphoid and Mucosal Sites

    Kumar BV*, Ma W*, et al (2017)
    Cell Reports

  2. Analyzing T cell repertoire diversity by high-throughput sequencing

    Grinshpun B et al (2013)
    Global Conference on Signal and Information Processing (GlobalSIP), IEEE