Statistical approaches for differential analyses on transcriptomics data

Relatore: Simone Tiberi (Università di Bologna)

  • Data: 19 gennaio 2023 dalle 16:00 alle 17:00

  • Luogo: Aula I - Via Belle Arti, 41

Transcriptomics data (notably, RNA-sequencing), allow measuring the mRNA abundance of genes and transcripts. Frequently, interest lies in identifying genes and transcripts displaying differences between experimental conditions (e.g., healthy vs. diseased or treated vs. untreated). Such differences refer to particular aspects of the data, such as overall gene abundance (i.e., differential gene expression) or splicing (i.e., differential splicing).
Analyzing transcriptomics data presents several challenges, due to biological noise (e.g., between transcripts, cells and samples), and technical limitations in the measurement process. For instance, most RNA-sequencing reads are compatible with multiple transcripts, making it difficult to estimate transcript abundance and, hence, to study transcript-level processes such as splicing.
In this seminar, I will illustrate three statistical methods, distributed as Bioconductor R packages, to perform various types of differential analyses from transcriptomics data.

Alessandro Baldi Antognini