Web Tool for Clinic Trio Based Sequence Data Analysis to Identify Potential Pathogenic Variants for Rare Genetic Diseases Öffentlichkeit

Johnson, Kevin (Spring 2022)

Permanent URL: https://etd.library.emory.edu/concern/etds/m039k613d?locale=de
Published

Abstract

An important tool in the diagnosis of rare genetic diseases is whole exome or genome sequencing (WES/WGS). It is believed that many rare genetic diseases are caused by rare variations in the patients’ genome. Typically, clinical WES/WGS is done for patients and their parents in an attempt to find potential pathogenic variations. Advanced bioinformatics skills are needed to analyze these WES/WGS data. Variant annotations about the variant position in a gene, biological functions, and possible pathogenicity need to be referred to from genomic databases. WES/WGS data with variant annotation need to be cleaned, filtered, and presented in a meaningful way. An automated web tool for the processing and analysis of trio-based WES/WGS data could help clinicians diagnose rare genetic diseases. I have developed a workflow process that automatically, which will create a table of possibly pathogenic variants and display the output table alongside the input WES/WGS data in a webtool. The tool makes the process of variant identification and visual review easier and quicker in the diagnosis of rare genetic diseases.

Table of Contents

Abstract...........4

Introduction.....6

Methods...........8

Results............15

Discussion.......20

Appendix A......24

References.......28

About this Master's Thesis

Rights statement
  • Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.
School
Department
Subfield / Discipline
Degree
Submission
Language
  • English
Research Field
Stichwort
Committee Chair / Thesis Advisor
Committee Members
Zuletzt geändert

Primary PDF

Supplemental Files