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BSU Seminar: ‘Statistical approaches for differential analyses on transcriptomics data’

December 13 @ 2:00 pm - 3:00 pm


Speaker: Dr Simone Tiberi, Universita di Bologna

Abstract: 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.

This will be a free hybrid seminar taking place at the MRC Biostatistics Unit. If you would like to attend virtually, please register here: 


December 13
2:00 pm - 3:00 pm
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MRC Biostatistics Unit


MRC Biostatistics Unit
East Forvie Building, Forvie Site, Robinson Way
Cambridge, CB2 0SR United Kingdom
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