NCSI: RNA Comparative Analysis of COVID-19 Strains

Status	Completed
Mentor Name	Stephen Wheat
Mentor's XSEDE Affiliation	Campus Champion
Mentor Has Been in XSEDE Community	1-2 years
Project Title	RNA Comparative Analysis of COVID-19 Strains
Summary	The student(s) will work with Biochem & CompSci faculty on a project aimed at understanding the patterns of the COVID19 mutations. It will include preparing the code, data capture and preparation, job configuration, job execution, and output assessments. It will also include evangelizing CI interests to one or more local high-schools.
Job Description	The primary work effort involves a research code developed at ORU for homology analytics. The student(s), as directed, trained, and assisted by faculty members from CSC and BioChem, will: 1) Collect Covid19 RNA sequences from public sources, cleaning/adjusting the sequences to FASTA or similar format, and resolving data flaws, if any; all to prepare the data sets for comparative analytics. 2) Configure ORU's homology code framework to do a parametric-driven comparison of the strains. 3) Collect the computational results, resolving any process issues. 4) Support R-based analysis of the patterns from the analysis 5) Document hypotheses, set up follow-on analytics to affirm. 6) Document findings into at least one paper for publication. 7) Assure the data is curated properly. An additional task is to survey local K-12 schools for interest and planning for developing Girls Who Code chapters for which the ORU Student ACM chapter would facilitate student tech ambassadors to be GWC facilitators working with the K-12 teachers at one or more schools.
Computational Resources	The analysis will primarily be done on ORU's HPC cluster, which is available to Oklahoma researchers as a virtual asset of the OneOCII working group. Any analysis that requires greater computational capability will be first taken to OU or OSU, and then to PSC, based upon the TBD computational load.
Contribution to Community	This project is one of many throughout the nation that are addressing different search paths into developing means to understand and mitigate the Covid19 pandemic. It also helps to inform and educate the local K-12 community on what can be done here in Tulsa of significant importance, giving real-world relatable examples of the impact/contribution of those working in CI-enabled research.
Position Type	Learner
Training Plan	Drs. Woerner and Wheat shall be the mentors for code development, HPC job management, and data analytics. This will be done through co-development and tutorial sessions that expand what is learned in the classroom. On-line training seminars will be utilized as well. For the first semester, the students will have an itemized agenda of skill development, mapped to resources and to project milestones. A good portion of the training will be accomplished in hands-on co-development, working side-by-side with faculty.
Student Prerequisites/Conditions/Qualifications	Students must have an interest in Data Science, but no prior course work is required. Prior course work is preferred. Students should be majoring in one of these: CSC, Data Science, BioChem, or equivalent.
Duration	Semester
Start Date	01/11/2021
End Date	04/30/2021