bioweek-r-data-handling-2019 - bioweek-r-data-handling-2019 - Training
|Date:||13.03.2019 9:00 - 13.03.2019 17:00|
|Location details:||The event is organised at the CSC Training Facilities located in the premises of CSC at Keilaranta 14, Espoo, Finland. The best way to reach us is by public transportation; more detailed travel tips are available.|
|lecturers:|| Bishwa Ghimire |
University of Helsinki
|The fee covers all materials, lunches as well as morning and afternoon coffees.|
The seats are filled in the registration order. If a cancellation is received five (5) business days prior to the course, the course fee will be refunded with the exception of a handling fee of 10 €. For no-shows and cancellations after the cut of date no refunds will be made. Registration can be transferred to someone else from the same organization without additional charge.
Payment can be made with electronic invoicing, credit card, or direct bank transfer. Note that for electronic invoicing you need the operator and e-invoicing address (OVT code) of your organization. Please also note that invoice reference is needed for electronic invoicing in your organization, so please have this available when registering.
The course is mainly targeted for biologists who need to get started with R for bioinformatics data analysis in the future. The course consists of R basics, data manipulation, making basic plots and more advanced visualizations.
The course content of the first session will be made available to the participants to familiarize with R basics before the course.
After the course the participants will have better understanding of data structures in R, be able to manipulate and convert the data to required format. Participants will also be able to understand their data better by using suitable visualization techniques.
It is recommended to go through the session-1 course material before the course to familiarize oneself R basics.
9:00 Session 1: Getting started (R basics)
- R introduction and installation
- R-studio overview
- Variables and operators
- Data types
- Reading and writing files
- Control structures
- Saving worspace
- R code - Best practices
10:00 Coffee break
10:30 Session 2: Data Manipulation
- Data frame slicing
- Merging data
- Data manipulation using dplyr
- Reshaping data
- Regular expression
13:00 Session 3: Basic visualization techniques
- Density plot
- Violin plot
- Hierarchical Clustering
- Volcano plot
- Plot components [optional]
- Colors [optional]
14:30 Coffee break
15:00 Session 4: Advanced visualization techniques
- Interactive 3D plots
- Correlation graph
- Circos plot
- Gene-set enrichment analysis [optional]