Genomic Analysis with R in 3 weeks

This repository contains materials for a 3-week course designed to introduce high school students (9th grade or higher) to data analysis using R with a focus on studies involving genetic data.

General Information

• Instructor: Gustavo de los Campos ( [email protected] )
• Modality: Synchronous distant learning (via discord)
• Required background: High school student, 9th grade or higher.
• Expected time commitment: 10-15 hr/week. We will meet as a group on Monday for a lecture and an introduction of the week's task, have a short lecture and office hours on Wednesday, and meet as a group on Friday to present and discuss results.
• Other requisites: Students are required to have access to a computer, have a personal Discord and Github accounts.
• Disclaimer:
  • The course is offered by Gustavo de los Campos.
  • This is not a Michigan State University course.
  • Upon completion, you will receive a certificate signed by the instructor.

Tentative program

• Week 1: Introduction to Github, R, and RStudio

  • Introduction to R: Types, conditional statements, loops, plots, arrays, and importing/exporting data.

  • Introduction to Github.

  • Reporting using RMarkdown and RStudio.

  • Task 1:

    • Reading a genomic data set in R.
    • Producing summary statistics for phenotypes and genotypes.
    • Report results.

• Week 2: Descriptive statistics and association analysis

  • Variance, covariance and correlation.

  • Simple linear regression.

  • Introduction to Genome Wide Association (GWA) Analysis.

  • Task 2:

    • Produce a Manhattan plot.
    • Identify SNPs significantly associated with a trait.
    • Report results.

• Week 3: Beyond single-marker-phenotype analysis:

  • Multiple-linear regression (models, estimation, and goodness of fit).

  • Training versus testing accuracy.

  • The curse of dimensionality.

  • Task 3:

    • Fit a multiple regression model to a training set (we will consider various approaches).
    • Evaluate prediction accuracy in the training and testing set.
    • Report results.

Reading materials

• Introduction to R:

  • RIntro in GitHub
  • R for Data Science
  • Too many youtube videos to be listed here!

• RMarkdown:

  • Template

• Introduction to GWAS:

  • Will add a couple of references here...

Data

Tentative Schedule

Date	Time	Activity	Matierials
M., July 19, 2021	5:00pm-6:00pm	Lecture
Wed., July 21, 2021	5:00pm-6:00pm	Q&A + short lecture
Fr., July 23, 2021	5:00pm-6:00pm	Presentation of Reports
M., July 26, 2021	5:00pm-6:00pm	Lecture
Wed., July 28, 2021	5:00pm-6:00pm	Q&A + short lecture
Fr., July 30, 2021	5:00pm-6:00pm	Presentation of Reports
M., August 2, 2021	5:00pm-6:00pm	Lecture
Wed., August 3, 2021	5:00pm-6:00pm	Q&A + short lecture
Fr., August 5, 2021	5:00pm-6:00pm	Presentation of Reports