Differentially expressed gene detection and analysis

  • Alessandro Cellerino
  • Michele Sanguanini
Part of the CRM Series book series (PSNS, volume 17)


RNA-seq analysis of gene expression delivers, for any given sample, an estimate of the the abundance of transcripts derived from a gene (expressed as number of reads mapping to that gene). However, in order to derive useful biological information from these high-dimensionality data, it is necessary to compare these data with those obtained from other samples that differ in some biological variable of interest (e.g., different tissues, conditions, time points, and so on). This requires a statistical model that—for each pairwise comparison—provides the probability (p-value) that the observed difference is due to chance (i.e. the probability that the measurements in the two groups are extracted from the same distribution). Only when this difference is significant (i.e. the p-value is sufficiently small), the gene can be defined as differentially expressed between the two conditions.


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Copyright information

© Scuola Normale Superiore Pisa 2018

Authors and Affiliations

  • Alessandro Cellerino
    • 1
  • Michele Sanguanini
    • 2
  1. 1.Scuola Normale SuperiorePisaItaly
  2. 2.Gonville and Caius CollegeUniversity of CambridgeCambridge, CambridgeshireUnited Kingdom

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