NYRaMP-Informatics-2024: Difference between revisions
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==Week 4. Aug 27== | ==Week 4. Aug 27== | ||
* R Demo I: [https://borreliabase.org/~wgqiu/tutorial-markdown.html#part-1.-t-test-for-two-groups Documentation & presentation with R Markdown (Part I)] | * R Demo I: [https://borreliabase.org/~wgqiu/tutorial-markdown.html#part-1.-t-test-for-two-groups Documentation & presentation with R Markdown (Part I)] | ||
* R Demo II: [https://borreliabase.org/~wgqiu/r-demo-2024.html#part-4.-advanced-topic-cluster-analysis-of-multi-dimensional-data Cluster analysis (Part 4)]; [https://borreliabase.org/~wgqiu/r-demo-2024.html#part-5.-case-study-differential-gene-expressions-in-lyme-diease-bacteria | * R Demo II: Advanced topics: [https://borreliabase.org/~wgqiu/r-demo-2024.html#part-4.-advanced-topic-cluster-analysis-of-multi-dimensional-data Cluster analysis (Part 4)]; [https://borreliabase.org/~wgqiu/r-demo-2024.html#part-5.-case-study-differential-gene-expressions-in-lyme-diease-bacteria Differential gene expression analysis (Part 5)] | ||
* Exit self-test | * Exit self-test | ||
Revision as of 20:35, 5 August 2024
| MA plot | Volcano plot | Heat map |
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Overview
A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and rapid DNA and RNA-sequencing technologies, biomedical sciences are undergoing a rapid & irreversible transformation into a highly data-intensive field, that requires familiarity with concepts in both biological, computational, and statistical sciences.
Genome information is revolutionizing virtually all aspects of life sciences including basic research, medicine, and agriculture. Meanwhile, use of genomic data requires life scientists to be familiar with concepts and skills in biology, computer science, as well as statistics.
This workshop is designed to introduce computational analysis of genomic data through hands-on computational exercises.
Learning goals
By the end of this workshop students will be able to:
- Visualize genomics data using R & RStudio
- Perform t-tests, regression analysis, and association tests with R & Rstudio
- Interpret results of data visualization & statistical analysis
Web Links
- Install R Base & R Studio (Desktop version): https://posit.co/download/rstudio-desktop/
- Textbook: Introduction to R for Biologists
- Download: R datasets
- A reference book: R for Data Science (Wickharm & Grolemund)
Week 1. Aug 6
- Pre-test: visualization, interpretation, and stats
- Computer setup & software download/installation
- R Tutorial 1. Getting started: Basics: interface, packages, variables, objects, functions
- Practice Quiz #1
Week 2. Aug 13
- R Tutorial 2. Data manipulation
- R Tutorial 3. Data visualization
- Practice Quiz #2
Week 3. Aug 20
- R Tutorial 4. t-tests & linear regression
- Practice Quiz #3
Week 4. Aug 27
- R Demo I: Documentation & presentation with R Markdown (Part I)
- R Demo II: Advanced topics: Cluster analysis (Part 4); Differential gene expression analysis (Part 5)
- Exit self-test