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Welcome to JianYang Lab!

We are a team of researchers focused on understanding genomic variation and its impact on human health. Our work involves developing advanced statistical methods to analyze genetic and omics data from large cohorts, with the aim of improving the diagnosis, treatment, and prevention of complex diseases.

Our research areas include genomic variation and population health, molecular mechanisms underlying complex traits and diseases, genomic risk prediction, cancer genomics, and the development of bioinformatics tools.

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  1. MeDuSA MeDuSA Public

    MeDuSA is a fine-resolution cellular deconvolution method that leverages scRNA-seq data as a reference to estimate cell-state abundance in bulk RNA-seq data.

    R 43 3

  2. gsMap gsMap Public

    Integrating GWAS and spatial transcriptomics for spatially resolved mapping of cells associated with human complex traits.

    Python 195 16

  3. GCTA GCTA Public

    C++ 8 3

  4. gsmr2 gsmr2 Public

    The gsmr R-package implements the GSMR (Generalised Summary-data-based Mendelian Randomisation) method that uses GWAS summary statistics to test for a putative causal association between two phenot…

    R 18 1

  5. PIGA PIGA Public

    Pangenome-Informed Genome Assembly (PIGA) workflow for population-scale diploid genome assembly

    Python 18

  6. spatial-vista-py spatial-vista-py Public

    Visualize 3D ST data in Jupyter

    JavaScript 12

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