22100 - R for Bio Data Science
This is the course website for the R for Bio Data Science course at section for Bioinformatics, Technical University of Denmark. If you wish to take the course without being enrolled at DTU, please click here for more information.
Course Programme
About
- Course responsible: Leon Eyrich Jessen
- Schedule: Spring F1A, i.e. on Mondays 8 - 12
- Location: Lyngby Campus, see course version above
- Exam: See DTU Examination timetable
- Text book: R for Data Science by Garrett Grolemund and Hadley Wickham
- Course Description: For full course description, please see the DTU Course Base
- Official GitHub site: https://github.com/rforbiodatascience
Collection of Additional Ressources
Open source books Please, feel free to explore the following books:
- Hands-On Programming with R by Garrett Grolemund
- Statistical Inference via Data Science - A moderndive into R and the tidyverse by Chester Ismay and Albert Y. Kim
- Introduction to Data Science, Data Analysis and Prediction Algorithms with R by Rafael A. Irizarry
- Mastering Shiny by Hadley Wickham
- An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
- STAT 545 - Data wrangling, exploration, and analysis with R by Jenny Bryan
Software Links
- The R Project for Statistical Computing
- RStudio - Open Source and Enterprise-ready professional software for R
- Tidyverse website
Some Useful Links
- R colour guide by Tian Zheng
- The tidyverse style guide - By Hadley Wickham
- RStudio Primers - Learn data science basics with the interactive tutorials
- The tidyverse style guide
- swirl - Learn R, in R
- RStudio Cheat Sheets
- RStudio Community - Stuck? Ask a question and get help moving on
- Presentations with ioslides
- HarvardX Biomedical Data Science Open Online Training
- Data Analysis Playlist
On Data Science
Guides on Good Data Practices
- A Guide to Reproducible Code by the British Ecology Society
- A Quick Guide to Organizing Computational Biology Projects
- How to pick more beautiful colors for your data visualizations
Suggested Data Sources
- datamicroarray: Small-sample, high-dimensional microarray data
- Assessment of the influence of intrinsic environmental and geographical factors on the bacterial ecology of pit latrines
- A New Way of Exploring Immunity - Linking Highly Multiplexed Antigen Recognition to Immune Repertoire and Phenotype
- Google Dataset Search
- Vanderbilt Biostatistics DataSets
- 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE
- BigOmics Analytics - Let's fight coronavirus infections together!