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)
- Learn how to use RStudio and R
- Learn basics of data visualization and exploratory data analysis
- Learn to use R Notebooks
-
Applied Bioinformatics and Computational Biology (ABCB), 8 weeks (2 credits)
- Learn the fundamentals of exploratory analysis of RNA-seq data, including PCA and clustering
- Learn the fundamentals of differential expression analysis, enrichment analysis, and visualization
- Practice and present on learned R skillset through published data via Capstone project.
- A recent computer running Windows 10/11, MacOS, or Linux (inform instructors if you have any concerns)
- Software installation prior to first class (instructions)
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)