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RNA-seq workshop course materials 11/10/2014

By Stephen Turner (100774)

Abstract

<p>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:</p> <p>1. Know how to provision your own computing resources using Amazon Web Services Elastic Compute Cloud.<br>2. Be familiar with the UNIX shell, including nagivating the filesystem, creating/examining/removing files, getting help, and batch operations.<br>3. Know how to align and quantitate gene expression with RNA-seq data.<br>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.<br>5. Know what packages to use and what steps to take to analyze RNA-seq data for differentially expressed genes.</p> <p>This book is a PDF version of the online materials available at http://bioconnector.github.io/workshops/. </p> <p>This course is sponsored by the Claude Moore Health Sciences Library, and borrows some materials from the Software Carpentry and Data Carpentry projects.</p> <p> </p

Topics: Bioinformatics, Computational Biology, bioinformatics, gene expression, rna-seq, tutorial
Year: 2014
DOI identifier: 10.6084/m9.figshare.1247658.v1
OAI identifier: oai:figshare.com:article/1247658
Provided by: FigShare
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