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postgraduate thesis: Development of a novel enrichment panel for sequencing and a tailored data analysis pipeline for molecular diagnosis of primary immunodeficiencies

TitleDevelopment of a novel enrichment panel for sequencing and a tailored data analysis pipeline for molecular diagnosis of primary immunodeficiencies
Authors
Advisors
Advisor(s):Lau, YLYang, W
Issue Date2022
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Yang, X. [杨幸天]. (2022). Development of a novel enrichment panel for sequencing and a tailored data analysis pipeline for molecular diagnosis of primary immunodeficiencies. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
AbstractPrimary Immunodeficiencies are a heterogeneous group of inborn disorders of immunity. Accurate molecular diagnosis has not been consistently achieved despite the power of next-generation sequencing technology. This study is aimed at improving the molecular diagnosis for primary immunodeficiency patients through the technological improvement of the sequencing process and the improvement in bioinformatics data analysis. In. this study, a workflow tailored for the molecular diagnosis of primary immunodeficiency patients was developed, composed of a new DNA sequence capture and enrichment panel, and a tailored Linux-based bioinformatic data analysis pipeline. The newly developed workflow brings in three major advantages compared to the widely-used current diagnosis workflow. First, the tailored enrichment panel was designed to continuously cover clinically important causal genes of primary immunodeficiencies. Combined with structural variants calling workflow in the tailored data analysis pipeline, we managed to include structural variants in our causal mutation detection process. Second, we added a short variant recall process to discover potentially important small variants in regions of segmental duplications in the human genome, which are not accessible by traditional variant calling tools. Third, we built an automated system using various variant annotation resources to rank variants based on the interpretation guidelines from The American College of Medical Genetics and Genomics. Compared with the results on a group of primary immunodeficiency patients processed by traditional whole-exome sequencing analysis, the improved molecular diagnosis workflow, composed of both a tailored enrichment panel and a tailored bioinformatic data analysis pipeline, achieved a significantly higher diagnosis rate. Moreover, the one-stop solution can be extrapolated to the molecular diagnosis of many other rare genetic diseases.
DegreeDoctor of Philosophy
SubjectImmunodeficiency - Molecular diagnosis
Dept/ProgramPaediatrics and Adolescent Medicine
Persistent Identifierhttp://hdl.handle.net/10722/341583

 

DC FieldValueLanguage
dc.contributor.advisorLau, YL-
dc.contributor.advisorYang, W-
dc.contributor.authorYang, Xingtian-
dc.contributor.author杨幸天-
dc.date.accessioned2024-03-18T09:56:09Z-
dc.date.available2024-03-18T09:56:09Z-
dc.date.issued2022-
dc.identifier.citationYang, X. [杨幸天]. (2022). Development of a novel enrichment panel for sequencing and a tailored data analysis pipeline for molecular diagnosis of primary immunodeficiencies. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/341583-
dc.description.abstractPrimary Immunodeficiencies are a heterogeneous group of inborn disorders of immunity. Accurate molecular diagnosis has not been consistently achieved despite the power of next-generation sequencing technology. This study is aimed at improving the molecular diagnosis for primary immunodeficiency patients through the technological improvement of the sequencing process and the improvement in bioinformatics data analysis. In. this study, a workflow tailored for the molecular diagnosis of primary immunodeficiency patients was developed, composed of a new DNA sequence capture and enrichment panel, and a tailored Linux-based bioinformatic data analysis pipeline. The newly developed workflow brings in three major advantages compared to the widely-used current diagnosis workflow. First, the tailored enrichment panel was designed to continuously cover clinically important causal genes of primary immunodeficiencies. Combined with structural variants calling workflow in the tailored data analysis pipeline, we managed to include structural variants in our causal mutation detection process. Second, we added a short variant recall process to discover potentially important small variants in regions of segmental duplications in the human genome, which are not accessible by traditional variant calling tools. Third, we built an automated system using various variant annotation resources to rank variants based on the interpretation guidelines from The American College of Medical Genetics and Genomics. Compared with the results on a group of primary immunodeficiency patients processed by traditional whole-exome sequencing analysis, the improved molecular diagnosis workflow, composed of both a tailored enrichment panel and a tailored bioinformatic data analysis pipeline, achieved a significantly higher diagnosis rate. Moreover, the one-stop solution can be extrapolated to the molecular diagnosis of many other rare genetic diseases.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.lcshImmunodeficiency - Molecular diagnosis-
dc.titleDevelopment of a novel enrichment panel for sequencing and a tailored data analysis pipeline for molecular diagnosis of primary immunodeficiencies-
dc.typePG_Thesis-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplinePaediatrics and Adolescent Medicine-
dc.description.naturepublished_or_final_version-
dc.date.hkucongregation2023-
dc.identifier.mmsid991044683805803414-

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