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VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
BEGIN:VEVENT
DTSTAMP:20260715T233756Z
UID:85a4c084-a47c-49ee-ba9d-9f115114bc42
DTSTART:20240402T090000Z
DTEND:20240409T170000Z
DESCRIPTION:Today it is possible to obtain genome-wide transcriptome data f
 rom single cells using high-throughput sequencing (scRNASeq). The main adv
 antage of scRNASeq is that the cellular resolution and the genome wide sco
 pe makes it possible to address issues that are intractable using other me
 thods\, e.g. bulk RNASeq or single-cell RT-qPCR. These scRNASeq datasets c
 an be used to unravel heterogenous cell populations\, for the discovery of
  new cell types and states\, the reconstruction of developmental trajector
 ies and fate decisions\, all previously masked in bulk transcriptome analy
 ses. However\, to analyze scRNASeq data\, novel methods are required and s
 ome of the underlying assumptions for the methods developed for bulk RNASe
 q experiments are no longer valid.
LOCATION:Antwerp - Campus Drie Eiken UAntwerpen\, Universiteitsplein 1
SUMMARY:Analysis of single cell RNASeq data
URL;VALUE=URI:https://training.vib.be/all-trainings/analysis-single-cell-rn
 aseq-data-5
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