Applied Genomics Analysis is a graduate level course at East Carolina University

Course objectives:

Applied Genomics Analysis focuses on the understanding and application of statistical genomics and bioinformatics through the lens of contemporary technologies and software. In this course, we gained a basic understanding of:

1. Genomics history and theory
2. R coding for genomics
3. Statistical genomics
4. Exploratory machine learning
5. Predictive modeling
6. Working with genomics intervals
7. Raw data QC/filtering/alignment
8. RNS-seq analyses
9. CHiP-seq analysis
10. DNA methylation analysis
11. Multi-omics analyses

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Contributors:

• Carol Gause
• Megan Linke

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Repo contents:

• Final_Project: A markdown file containing information about the ABBA-BABA test we conducted for our final project.
• PresentationSlides:
  • FinalProject_Popgenomics_2023.pdf: PDF file of presentation slides created by Carol Gause & Megan Linke.
  • Operations on Genomic Intervals.pdf: PDF file of presentation slides created by Carol Gause.
• bin:
  • jackKnife.R: An R script for jackknifing written by Anders Albrechtsen.
• results: Output files from our final project.