Created by Olga Dethlefsen & Ståle Nygård. Parts of the code were adapted from, courtesy of Åsa Björklund

Content overview

Learning objectives

What is differential expression testing

  • taking read count data &
  • performing statistical analysis to discover quantitative changes in expression levels between experimental groups
  • i.e. to decide whether, for a given gene, an observed difference in read counts is significant (greater than what would be expected just due to natural random variation)

DE is an “old problem”

  • known from bulk RNA-seq and microarray studies
  • in fact building on one of the most common statistical problems, i.e comparing groups for statistical differences

Single-cell vs bulk RNA-seq count matrices


Characteristics of scRNA-seq data

Example distributions


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