Training

Course overview

Participants will receive a basic understanding of the R syntax and ability to manipulate R objects. After this course students should feel comfortable with the R/Bioconductor environment and be in a position to continue their own explorations of the functionality of R and start using R for their basic biostatistics needs. You will understand why Quality Control of microarray is necessary, run a QC workflow and be able to correctly interpret the results. A range of data exploration methods will be reviewed (Principal Component Analysis, Hierarchical clustering, Scatter plots).

Audience

This course is aimed at researchers and scientists (PhD students, post-doc, staff scientist) who will benefit from an introduction to microarray data analysis and training in how to perform simple analyses using R/Bioconductor.

All sessions are a combination of lectures and hands-on. Prerequisites are a life science degree or equivalent experience, basic understanding of microarray techniques, and a basic understanding of biostatistics. No prior knowledge of R or Bioconductor is assumed.

Syllabus, Tools and Resources

During this course you will learn about:

• Data standards: Metadata, MIAME 2.0, Isa software suite

• Data generation: Microarray technology

• Data analysis: QC & data exploration using R and Bioconductor

Learning Objectives

After this course you should be able to:

• Identify an R function or operation and describe its use

• Apply functions and operations to achieve a specific result in R

• Recognize the importance of Metadata

• Run and correctly interpret a QC workflow

• Explore your data using PC, HC, and scatter plots