ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
Data visualization
20 January 2020
For-profit: 600 CHF
No future instance of this course is planned yet
The course is now full and with a long waiting list. You you do not want to miss your chance to be part of the next session and remain informed about all training activities at SIB, we highly recommend you to keep an eye on our list of upcoming events (https://www.sib.swiss/training/upcoming-training-courses) and subscribe to our courses mailing list here (if not yet done): https://lists.sib.swiss/mailman/listinfo/courses. Thank you for your understanding.
Overview
Scientific results are mostly conveyed through graphics and tables, and representing data graphically in a clear way is an important task for any scientist.
Creating such graphs is not a trivial task though and choosing the right representation depends on many factors: among the most important the data itself, the message that the researcher wants to get across, and the way in which the data is presented (a figure in an article is completely different from a figure in slides).
During this course, we will present different ways for representing data, how to choose among them, why you should avoid using error bars, how to design efficient graphs, which tools to use (and which tools to avoid !), how to design graphs for specific media, good practices for plotting data, and common mistakes to avoid.
This course will also include practicals using the R statistical software; during these practicals, we will discuss and introduce the differents models for creating graphics in R (including base R and ggplot2).
Audience
This course is addressed to scientists who need to produce data visualization and who have already used the R software before.
Learning objectives
At the end of the course, the participants are expected to:
- apply data visualisation methods to represent their data and get their message across
- choose the right method to represent a dataset graphically
- use the R software (base R and ggplot2) to produce data visualizations
Prerequisites
Knowledge / competencies
This course is designed for beginners in R, for instance those who have attended any of the SIB courses on First Steps in R.
Technical
You are required to bring your own laptop with a wifi connection, and the following software installed PRIOR to the course: R, R Studio. A list of packages will be provided in due time.
Application
The registration fees for academics are 120 CHF and 600 CHF for private companies. This includes course content material and coffee breaks.
Deadline for registration and free-of-charge cancellation is set is set to 20/01/2020. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to our general conditions.
You will be informed by email of your registration confirmation.
Venue and Time
University of Lausanne, Amphimax building, classroom 412 (Metro M1 line, Sorge station).
The course will start at 9:00 and end around 17:00. Precise information will be provided to the participants on due time.
Additional information
Trainer: The course will be taught by Frédéric Schütz, PhD, from the SIB Bioinformatics Core Facility in Lausanne.
Coordination by Patricia Palagi.
We will recommend 0.5 ECTS credits for this course (given a passed exam at the end of the course).
You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
For more information, please contact training@sib.swiss.