# ??package_name
# example, to know more about readr
??readrR Resources
R リソース
Important R resources for biological data analysis
Biological and other data analysis skills in R require to understand the basics of the subject, learn coding and how to use RStudio. It is also recommended to take advantage of the extensive R ecosystem and use a variety of R packages to help us with the data analysis. Please see the resources below.
R & RStudio have extensive support including community and research fora, AI tools, etc. If you encounter any issues with installing R packages, have programming or analysis problems, please explore them. There are also various books and tutorials that can be used for learning R.
- Community support
- AI Chat
- Research fora
- Books & Tutorials (Free)
R/RstudioSet-upRfor Excel UsersRStudioEducation- Posit Cheatsheets
Rfor Data Science (2nd Edition / free PDF)Rfor Data Science (1st Edition / paper copy) available in English /Japanese / Chinese at Bioinformatics Laboratory (P404)
There are over 20,000 actively developed R packages that help performing a variety of analysis, such as data import, manipulation, visualization and more. Below is a short list of useful R package.
- Collection of Data Science Packages
- Data Import & Writing
readxlreadr
- Data Manipulation (wrangling)
dplyrtidyr
- Data Visualization
ggpubrggplot2
- Data Exploration
- Public Database API
- Differential Gene Expression
- Gene Set Enrichment Analysis
- Single Cell Data Analysis
- Heatmaps
- Principal Component Analysis (PCA)
- Web Application Creation
- Classification and Regression Training (ML)
- Survival Analysis
To learn more about the packages, type and execute the following code in your RStudio console: