2014 Half-Day R Camp

Computational Biology Research Camp for High School Students

R and Gene expression

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Overview: This camp provides statistical methods in the context of disease research. R is a statistical tool and programming language, useful in various application areas such as medicine, public policy, and economics. After introducing basics of R, the camp will apply R to statistically analyze RNA expression data of Ebola-infected samples. No prior knowledge is needed but concept of RNA expressions will be beneficial. Lunch is included in the fee. Bring your laptops. Bring your laptops.

 

NOTE: We changed our disease of focus for this camp to Ebola from Parkinson’s disease.

 

DATE: December 20, 2014     TIME: 9:30 am – 1:30 pm

 

LOCATION: Room 1690 Bob and Betty Beyster Building, University of Michigan, 2260 Hayward Street, Ann Arbor, MI 48109

 

FEE: $50

 

MAIN TARGETS: high school students (young women and men) who are intereted in computer, math, biology, and medicine.

 

Sponsor: Women In Science and Engineering (WISE)

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Registration Form

You will recieve email confirmation of the registration.

 

Goals

  1. Expose high school students to the emerging era of medical genomics, when all doctors must be well-acquainted with genetic discoveries, technologies, and applications.
  2. Support GIDAS (Genes In Diseases And Symptoms) club members for in-depth knowledge in the field.

Tentative Agenda

  • 9:15 am – 9:30 am
Check in
  • 9:30 am – 10:30 am
Basics of R
Calculation, Variable, Vector, Matrix, Function
Goal: Understand basic programming concept
  • 10:30 am- 11:00 am
Practice R
Simple calculations using R
Goal: Be able to calculate gene expression data using R
  • 11:00 am – 11:30 am
R Function Competition
Play games to memorize R functions
Goal: Become familiar with statistics and R
  • 11:30 am – noon
R Graphs
Visualize data using R
Goal: Make graphs using R
  • noon – 12:30 pm
Grab Lunch
  • 12:30 pm – 1:30 pm
Heat map generation using R
Statistical calculation of gene expression data from Ebola-infected samples
Goal: Understand statistics in graphs