2. Data analysis¶
This R project provides R scripts and R notebooks to perform basic analyses on survival datasets.
IPython notebooks that include all the environment setup and data analysis steps in simplified workflows are also provided in the main directory. It is the easiest way to get started 😃.
This section summarizes details these tools to help you choose the most appropriate solution for your project.
Note
Try to keep the code, data and result organized along the existing directory tree:
survival_analysis
|── bin Executable scripts
|── figs Figures
|── notebooks R notebooks
|── packrat R packages
|── templates Contains the spreadsheet template for data collection
|── docs Contains the files to build the sphinx documentation
|── lib Contains code librairies for notebooks and scripts
└── data Data files
See also
The C. elegans drug response tutorial is a great way to start!
R scripts¶
- Location
bin/directory.- When to use
For analyses that will repeat many times.
- When not to use
For custom analyses that will repeate only once.
When the details of the analysis process have to be showcased.
When testing new methods.
- Documentation
R notebooks¶
- Location
notebooks/directory.- When to use
For custom analyses that will repeate only once.
Whenever the details of the analysis process have to be showcased.
When testing new methods.
- When not to use
For analyses that will repeat many times.
- Documentation
IPython notebooks¶
- Location
Main directory of the project.
- When to use
Whenever keeping a trace of the global analysis process is needed.
In general, whenever using R scripts is appropriate.
- When not to use
In general, when using a R notebook is appropriate.
- Documentation