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SUMMARY:BSU Seminar: &quot\;Statistical approaches for differential analys
 es on transcriptomics data&quot\; - Dr Simone Tiberi\, Universita di Bolog
 na
DTSTART:20230110T140000Z
DTEND:20230110T150000Z
UID:TALK193861@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:Transcriptomics data (notably\, RNA-sequencing)\, allow measur
 ing the mRNA abundance of genes and transcripts. Frequently\, interest lie
 s in identifying genes and transcripts displaying differences between expe
 rimental conditions (e.g.\, healthy vs. diseased or treated vs. untreated)
 . Such differences refer to particular aspects of the data\, such as overa
 ll gene abundance (i.e.\, differential gene expression) or splicing (i.e.\
 , differential splicing). \nAnalyzing transcriptomics data presents severa
 l 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 transcri
 pts\, making it difficult to estimate transcript abundance and\, hence\, t
 o study transcript-level processes such as splicing. \nIn this seminar\, I
  will illustrate three statistical methods\, distributed as Bioconductor R
  packages\, to perform various types of differential analyses from transcr
 iptomics data.
LOCATION:Large Seminar Room\, East Forvie Building\, Forvie Site\, Robinso
 n Way\, Cambridge CB2 0SR
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