New statistical approaches to mapping the functional impact of HLA alleles in multimodal complex disease datasets

HLA等位基因与一系列免疫介导的性状相关。该项目旨在结合遗传学、编程、统计学和多模态数据集成等技术，以了解这些疾病相关HLA等位基因的功能影响。多模态单细胞功能基因组学的最新发展为在单细胞分辨率上理解HLA等位基因的影响提供了新的机会。在这个项目中，我们将开发新的统计技术，如高维高斯过程，来分析多模态数据，以了解HLA等位基因对细胞表型的影响。我们将把这些方法应用于传染病患者现有的多模态单细胞数据，以及炎症性肠病患者肠道活检中的微生物组和基因表达。在这两种情况下，目的是确定HLA等位基因在特定生物学背景下的功能影响。

HLA alleles are associated with a range of immune-mediated traits. This project aims to combine skills in genetics, programming, statistics and integration of multimodal data in order to understand the functional impacts of these disease-associated HLA alleles. Recent developments of multimodal single-cell functional genomics offer new opportunities to understand the impact of HLA alleles at single cell resolution. In this project, we will develop new statistical techniques, such as high-dimensional Gaussian processes, to analyse multimodal data to understand the impact of HLA alleles on cellular phenotype.We will apply these methods to existing multi-modal single-cell data from infectious disease patients, and to microbiome and gene expression in intestinal biopsies of inflammatory bowel disease patients. In both cases, the aim is to determine the functional impact of HLA alleles in specific biological contexts.