Applied Bioinformatics

Welcome to the Applied Bioinformatics course offered at The Scripps Research Institute.

Instructors: Dr. Andrew I Su (@andrewsu)
Teaching Assistants (TAs):

• Kai-Yu Chen (@chvbs2000)
• Carolina Gonzalez (@Carolina1396)
• Shashank Nagaraja (@dapluggg)
• Roger Tu (@turoger)

This course is available in 2 parts and operates under the Computational Biology & Bioinformatics (CBB) core track:

• Fundamentals of Scientific Computing, 4 weeks (1 credit)
  

  1. Learn how to use RStudio and R
  2. Learn basics of data visualization and exploratory data analysis
  3. Learn to use R Notebooks

• Applied Bioinformatics and Computational Biology (ABCB), 8 weeks (2 credits)

  1. Learn the fundamentals of exploratory analysis of RNA-seq data, including PCA and clustering
  2. Learn the fundamentals of differential expression analysis, enrichment analysis, and visualization
  3. Practice and present on learned R skillset through published data via Capstone project.

Prerequisites

• A recent computer running Windows 10/11, MacOS, or Linux (inform instructors if you have any concerns)
• Software installation prior to first class (instructions)

Course Materials

This section will be updated as the course progresses.

• Tuesday 2022-09-06: Course intro
  • slides
  • Homework due Monday 2022-09-12 3PM PT
• Thursday 2022-09-08: Data visualization
  • slides
  • Homework due Monday 2022-09-19 3PM PT
• Tuesday 2022-09-13:
  • slides
  • Homework due Monday 2022-09-19 3PM PT
• Thursday 2022-09-15:
  • slides (to be posted)
  • Homework due Monday 2022-09-26 3PM PT

Credit to past instructors and TAs: Dr. Sabah Ul-Hasan (@sabahzero), Dr. Huitian Yolanda Diao (@Huitian), Dr. Karthik Gangavarapu (@gkarthik), Shang-Fu Chen (@ShaunFChen), Jerry Zak (@trebbiano)