Analysis workflow for publicly available RNA-sequencing datasets

Differential gene expression analysis is widely used to study changes in gene expression profiles between two or more groups of samples (e.g., physiological versus pathological conditions, pre-treatment versus post-treatment, and infected versus non-infected tissues). Researchers at Universidad de Buenos Aires describe a protocol to identify gene expression changes in a pre-selected set of genes associated with severe acute respiratory syndrome coronavirus 2 viral infection and host cell antiviral response, as well as subsequent gene expression association with phenotypic features using samples deposited in public repositories. For complete details on the use and outcome of this informatics analysis, please refer to Bizzotto et al. (2020).

  • Publicly available COVID-19 RNA-seq datasets can be analyzed with R-based protocols
  • This protocol provides a quick and easy way to study gene expression dysregulations
  • The codes for plotting different types of analytical graphs are described
  • The present bioinformatic pipeline can be adapted to other datasets

Sanchis P, Lavignolle R, Abbate M, Lage-Vickers S, Vazquez E, Cotignola J, Bizzotto J, Gueron G. (2021) Analysis workflow of publicly available RNA-sequencing datasets. STAR Protoc 2(2):100478. [article]

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