May Institute: Computation and statistics for mass spectrometry and proteomics

May 1-12, 2017, Northeastern University, Boston MA
Organizers : Meena Choi and Olga Vitek

 

Description

In this course participants will explore key principles of creating and designing data visualizations with the ggplot2 graphing library in R. The module will use case studies with data from large-scale quantitative mass spectrometry-based proteomic experiments, however the design principles will more broadly apply. Specific topics include effective composition and layout of different visualizations, effective use of color, general strategies for working with different types of plots and charts, improving figure clarity, and techniques for visualizing multidimensional data. Through a mixture of lecture and hands-on activities, participants will be invited to consider the ways in which good design can help communicate the information.

Target audience

    Target audience are experimental scientists, bioinformaticians, computer scientists, data scientists, statisticians or engineers, interested in visualizing data in general, and quantitative proteomic data in particular. A minimal prior exposure to R (e.g., with the course ‘Beginner’s statistics in R’) is expected.

Reference

‘Points of View’ in Nature Methods

Speakers

  • Keynote: Michelle Borkin, Nils Gehlenborg
  • Instructors: Steven Braun, Ting Huang