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DTSTAMP:20260616T130049Z
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DTSTART:20230529T090000Z
DTEND:20230530T123000Z
DESCRIPTION:This hands-on course in Zoom introduces single-cell RNA-seq (sc
 RNA-seq) data analysis methods. It covers the processing of transcript cou
 nts from quality control and filtering to dimensional reduction\, clusteri
 ng\, cell type identification and cluster marker gene detection. You will 
 also learn how to do integrated analysis of multiple samples.Practicalitie
 sBoth course days are 9:00-12:30 Finnish time (8:00-11:30 CET).The course 
 consists of lectures and exercises. The lectures will be pre-recorded\, an
 d participants are requested to view the videos prior to the course and te
 st their knowledge with a set of questions. This gives you more time to re
 flect on the concepts so that you can use the classroom time more efficien
 tly for discussions and exercises.PrerequisitiesIn the exercises we use Se
 urat tools embedded in the free and user-friendly Chipster software\, so n
 o experience in R is required\, and the course is thus suitable for everyb
 ody who is planning to use single-cell RNA-seq.ContentYou will learn how t
 operform quality control and filter out low quality cellsnormalize gene ex
 pression valuesremove unwanted sources of variationselect highly variable 
 genes and perform dimensionality reduction (PCA)cluster cellsvisualize clu
 sters using UMAP and tSNEidentify cell types using reference-based SingleR
 find marker genes for a clusterintegrate multiple samplesfind conserved cl
 uster marker genes for two samplesfind genes which are differentially expr
 essed between two samples in a cell type specific mannervisualize genes wi
 th cell type specific responses in two samplesCourse materialsLinks to sli
 des\, lecture videos and exercisesTrainersMaria Lehtivaara\, Eija Korpelai
 nen and Iida Hakulinen (CSC)Price60 eurosMore informationShould you have a
 ny questions\, please don't hesitate to contact chipster@csc.fi.
LOCATION:Online
SUMMARY:Single-cell RNA-seq data analysis using Chipster
URL;VALUE=URI:https://ssl.eventilla.com/scrnaseq2023
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