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

绘制多模式复杂疾病数据集中 HLA 等位基因功能影响的新统计方法

• 批准号: 2748611
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2748611
• 关键词: New; statistical; approaches; mapping; functional

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.

HLA等位基因与一系列免疫介导的性状相关。该项目旨在联合收割机的遗传学，编程，统计和多模态数据的整合技能，以了解这些疾病相关的HLA等位基因的功能影响。多模式单细胞功能基因组学的最新发展为理解HLA等位基因在单细胞分辨率下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现有的多模态单细胞数据，从感染性疾病患者，并在肠道活检炎症性肠病患者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。