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RNA-Seq Data Analysis Protocol: Combining In-House and Publicly Available Data

  • Marc W. Schmid
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1669)

Abstract

Comparing gene expression profiles measured in a wide range of different tissue types, at different developmental stages, or under different environmental conditions can yield valuable insights into the mechanisms of cell/tissue specification and differentiation, or identify cell/tissue-type specific responses to environmental stimuli. Critical for such comparisons is the identical processing of data from different sources. This may also include the integration of a novel data set into an existing collection of data sets (e.g., in-house and publicly available data). Here, I describe a complete workflow for RNA-Seq data, from data processing steps to the comparison of gene expression profiles measured with RNA-Seq. I use publicly available data for demonstration purposes, but I also describe how to integrate your own data sets. The workflow runs on all three major operating systems (Linux, MacOS, and Windows). The scripts and the tutorial can be accessed on github.com/MWSchmid/RNAseq_protocol.

Key words

RNA-Seq Public data Data integration Analysis Differential expression Multigroup comparisons Gene expression Transcriptome Workflow 

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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Department of Evolutionary Biology and Environmental StudiesUniversity of ZurichZürichSwitzerland
  2. 2.Department of Plant and Microbial BiologyUniversity of ZurichZürichSwitzerland
  3. 3.URPP Global Change and BiodiversityUniversity of ZurichZürichSwitzerland
  4. 4.S3ITUniversity of ZurichZürichSwitzerland

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