Browsing by Subject "Sequence Analysis, DNA"
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Item Clinical Diagnostic Potential and Characterization of Distinctly Hypermutated Antibodies in Multiple Sclerosis Patients(2016-08-12) Rounds, William Harold Alexander; Cowell, Lindsay G.; Monson, Nancy L.; Wakeland, Edward K.; Patrie, Steven M.; Ward, E. SallyMultiple sclerosis (MS) diagnosis primarily revolves around the use of brain lesion detection by MRI and the elimination of other possible neurological disorder diagnoses through clinical testing and history. For many patients first experiencing clinical symptoms that could be MS-related, this presents a challenge since diagnostic certainty based on clinical presentation and testing does not always reach a consensus among doctors who evaluate them. With a growing body of evidence for B cell involvement and dysregulation in MS, our group investigated and identified a potential biomarker in the cerebrospinal fluid of patients with MS based on B cell antibody sequencing. This work first identified a distinct mutation pattern in the antibody sequences of CSF-derived B cells, termed the antibody gene signature (AGS), that could be used to identify patients with MS or patients who would convert to MS subsequent to their first onset of clinically detectable symptoms. This thesis project outlines the transition from AGS testing in a laboratory setting to its use and implementation as an additional clinical diagnostic tool for MS (MSPrecise®) using next generation sequencing (NGS). One of its main goals is to thoroughly evaluate the performance of MSPrecise® using the far greater throughput which NGS allows for. Over the course of the project, NGS technology and accuracy optimization methods have advanced significantly. As our laboratory is the first to ever utilize NGS for somatic hypermutation evaluation, we focused strongly on the evaluation of challenges and features associated with NGS use for immune repertoire diversity and somatic hypermutation profiling of clinical samples. In this context, this project also highlights observations on sequence library preparation and post-sequencing data filtering that affect all immune repertoire research that uses these rapidly developing sequencing platforms.Item High-Performance Software Development for Genomic Sequence Alignment and Analysis(2023-05-01T05:00:00.000Z) Zhang, Yun; Zhan, Xiaowei; Kim, Daehwan; Li, Bo; Wang, Tao; Hon, Gary C.Nucleic acid sequencing technology is a powerful tool for understanding genetic information. Genomic data analysis software is critical for transforming complex sequencing results into meaningful biological information. Emerging sequencing technologies help scientists to understand biological processes from multiple angles, but they also raise the challenge of developing new sequence analysis tools, especially new alignment methods, to support these techniques. In this dissertation, I developed a rapid and accurate sequence alignment software, HISAT-3N, to solve the alignment problem of nucleotide conversion sequencing (NC) technologies. NC technologies, such as BS-seq and SLAM seq, involve converting one type of nucleotide to another, which allows researchers to identify specific chemical modifications in DNA or RNA molecules. However, the conversions generated in these NC technologies make it difficult to align the reads back to the reference genome. To solve this issue, I implemented the 3-letter alignment algorithm into HISAT2, which was developed by our lab previously, to create HISAT-3N. I thoroughly tested HISAT-3N and demonstrated that it is more than seven times faster and more accurate than widely used sequence aligners, and can support all types of nucleotide conversion sequencing technologies, including those that have not yet been developed. Additionally, to generalize the process of developing new alignment methods to support new sequencing technologies, I created a platform that allows for the modularized design of sequence alignment software. This platform incorporates algorithms from HISAT2, STAR, and BWA, providing greater efficiency for developers to create novel sequence alignment software and more flexibility for users to analyze different types of data in a variety of computational environments. Finally, I developed a metagenomics analysis pipeline that effectively organizes and manages multiple well-known sequence analysis software for rapid and accurate soil microbial analysis. The successful development and implementation of these tools demonstrate the robustness of a well-designed bioinformatics software and pipeline framework in bioinformatics analysis. Overall, my work emphasizes the significance of continuously improving genomics data analysis tools. This is important to support emerging sequencing technologies and deliver more precise results, which assist researchers in revealing valuable genetic information.Item [UT Southwestern Medical Center News](2009-12-16) Piloto, Connie