Date of Graduation
5-2021
Document Type
Thesis
Degree Name
Bachelor of Science in Computer Engineering
Degree Level
Undergraduate
Department
Computer Science and Computer Engineering
Advisor/Mentor
Thompson, Dale
Committee Member/Reader
Steven, Ricke
Committee Member/Second Reader
Patitz, Matthew
Abstract
Bioinformatic analysis is a time-consuming process for labs performing research on various microbiomes. Researchers use tools like Qiime2 to help standardize the bioinformatic analysis methods, but even large, extensible platforms like Qiime2 have drawbacks due to the attention required by researchers. In this project, we propose to automate additional standard lab bioinformatic procedures by eliminating the existing manual process of determining the trim and truncate locations for paired end 2 sequences. We introduce a new Qiime2 plugin called TruncTrimmer to automate the process that usually requires the researcher to make a decision on where to trim and truncate manually after importing and demultiplexing sequences in the Qiime2 pipeline. By automating this process and removing the need for manual interaction by the researcher, this plugin provides another opportunity to automate another standard bioinformatic analysis procedure.
Keywords
Qiime2, Bioinformatics, Microbiome, TruncTrimmer
Citation
Lawless, Z. G., Dittoe, D., Thompson, D. R., & Ricke, S. C. (2021). TruncTrimmer: A First Step Towards Automating Standard Bioinformatic Analysis. Computer Science and Computer Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/csceuht/94
Included in
Bioinformatics Commons, Food Microbiology Commons, Numerical Analysis and Scientific Computing Commons, Other Computer Sciences Commons, Theory and Algorithms Commons