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Testing for differential expression 2014

Testing for differential expression 2014

Owned by Dhivya Arasappan
Last updated: May 24, 2015

Objectives

Once we've obtained abundance counts for our genes/exons/transcripts, we are usually interested in identifying those genes/exons/transcripts that are differentially expressed. 

In this section, you will learn about 4 different tools for identifying differentially expressed genes from gene count data. The same data from the previous exercises will be used. The data contains 75 bp paired-end reads that have been generated in silico to replicate real gene count data from Drosophila. The data simulates two biological groups with three biological replicates per group (6 samples total). 

  • Learn about DESeq, edgeR, DEXSeq and cuffdiff packages and the differences among these packages.
  • Becom