Biostatistics and Bioinformatics

我的研究项目包括多个项目，这些项目都是为了解决现实世界的问题，并专注于开发新的统计方法和软件来分析复杂的大数据。以下是我将领导或共同领导的几个研究项目的例子。1. 为第一个分析管道开发统计方法，使用单细胞基因组数据发现细胞类型丰度生物标志物，并在大规模研究中使用大量基因组数据验证生物标志物。我们的研究不仅将为数据分析提供一个软件管道，而且还将作为一个实验方案，指导基因组学研究人员利用单细胞和大量基因组学技术的优势，发现和验证细胞类型丰度生物标志物。我们将利用这一分析管道开发首个治疗慢性阻塞性肺疾病（COPD）的免疫疗法。基因组BC SIP（2021-2023）资助了本研究的第一阶段。我将申请更多的资金来继续它。2. 开发基因组诊断测试的新算法，以识别葡萄藤中的病毒感染。我们快速且经济的基因组解决方案将取代目前在葡萄藤上进行的30多种分子和生物检测来寻找疾病。加拿大葡萄认证网络将使用这种基因组测试来监测国内培育的葡萄藤，确保葡萄种植者能够更快、更经济地获得清洁的葡萄藤，以改善葡萄园的健康状况。（项目资助：Genome Canada GAPP 2021-2024）开发新的机器学习工具，研究40年来在6个沿海省份的14,710个贝类采集点收集的丰富时空数据。这些数据包括与气候变化、污染、沿海富营养化等因素相关的粪大肠菌群和引起健忘、腹泻和麻痹性贝类中毒的海洋生物毒素（ASP、DSP、PSP）。这项研究的成果将使加拿大政府机构（如NRC、ECCC、DFO、CFIA）和贝类行业能够可视化历史和地理空间污染模式，并预测加拿大未来的污染水平，以确保该行业的可持续性。它还可能影响政府未来的环境保护政策。（NRC DHGA项目2021-2023资助）

My research program comprises multiple projects, all motivated by solving real-world problems and focusing on developing novel statistical methods and software to analyze complex and big data. Following are a few examples of research projects I will lead or co-lead. 1. Develop the statistical methods for the first analysis pipeline to discover cell type abundance biomarkers using single-cell genomic data, and to validate biomarkers using bulk genomics data in large-scale studies. Our research will not only provide a software pipeline for data analysis, but also serve as an experimental protocol to guide genomics researchers in utilizing advantages from both single-cell and bulk genomics technologies to discover and validate cell type abundance biomarkers. We will apply this analysis pipeline to develop the first immunotherapy to cure chronic obstructive pulmonary disease (COPD). Genome BC SIP (2021-2023) funded the first stage of this research. I will apply for more funding to continue it. 2. Develop novel algorithms for a genomic diagnostic test to identify virus infections in grapevines. Our rapid and cost-effective genomic solution will replace the over 30 molecular and biological tests currently performed on grapevines to look for disease. The Canadian Grapevine Certification Network will use this genomic test for monitoring domestically bred vines, ensuring grape growers have faster and more affordable access to clean vines to improve the health of their vineyards. (Funded by Genome Canada GAPP 2021-2024.)3. Develop novel machine learning tools to investigate rich spatial-temporal data collected over 40 years on 14,710 shellfish harvesting sites across 6 coastal provinces. These data include fecal coliform bacteria and marine biotoxins that cause amnesic, diarrhetic and paralytic shellfish poisonings (ASP, DSP, PSP) associated with climate change, pollution, coastal eutrophication and other factors. The deliverables of this research will enable Canadian government agencies (e.g. NRC, ECCC, DFO, CFIA) and the shellfish industry to visualize historical and geospatial contamination patterns and to predict future contamination levels across Canada, to ensure the sustainability of this industry. It might also affect future government policies on environmental protection. (Funded by NRC DHGA program 2021-2023)