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RNA-seq workshop course materials 11/10/2014

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journal contribution
posted on 20.11.2014, 21:56 by Stephen Turner

This book contains material from a workshop directed toward life scientists with little to no experience with statistical computing or bioinformatics. This will introduce both the Linux/UNIX operating system and the R statistical computing environment, with a focus on a biological application - analyzing RNA-seq data for differentially expressed genes. The first half will introduce basic operation in a UNIX environment, and will cover the first steps in an RNA-seq analysis including QC, alignment, and quantitation. The second half will introduce the R statistical computing environment, and will cover differential gene expression analysis using Bioconductor. At the end of the course or after reading through this book, you will:

1. Know how to provision your own computing resources using Amazon Web Services Elastic Compute Cloud.
2. Be familiar with the UNIX shell, including nagivating the filesystem, creating/examining/removing files, getting help, and batch operations.
3. Know how to align and quantitate gene expression with RNA-seq data.
4. Become familiar with the R statistical computing environment, including data types, variables, array manipulation, functions, data frames, data import/export, visualization, and using packages.
5. Know what packages to use and what steps to take to analyze RNA-seq data for differentially expressed genes.

This book is a PDF version of the online materials available at http://bioconnector.github.io/workshops/. 

This course is sponsored by the Claude Moore Health Sciences Library, and borrows some materials from the Software Carpentry and Data Carpentry projects.

 

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