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DTSTAMP:20260618T204019Z
UID:aaa297c2-7225-4064-961f-70a420bd279e
DTSTART:20220406T090000Z
DTEND:20220408T120000Z
DESCRIPTION:This hands-on course introduces the participants to RNA-seq dat
 a analysis methods\, tools and file formats. It covers the whole workflow 
 from quality control and alignment to quantification and differential expr
 ession analysis. Both whole transcript and QuantSeq 3' UMI data are covere
 d. QuantSeq data analysis involves different preprocessing\, so the full s
 ession on 8.4.2022 is dedicated to analyzing QuantSeq data and you have th
 e option to register for that day only if you are already familiar with t
 he othe topics (please see the details below).The course consists of lectu
 res and exercises. The lectures will be pre-recorded\, and participants ar
 e requested to view the videos prior to the course and test their knowledg
 e with a set of questions. This gives you more time to reflect on the conc
 epts so that you can use the course time more efficiently for discussions 
 and exercises. Note that the lectures specific to QuantSeq data are given 
 during the course on 8.4.2022.The course takes place at 9-12 Helsinki time
  (8-11 CET) each day in Zoom.PrerequisitiesIn the exercises we use analysi
 s tools embedded in the free and user-friendly Chipster software\, so no p
 revious knowledge of Unix or R is required\, and the course is thus suitab
 le for everybody who is planning to use RNA-seq.Content6.4.2022 at 9-12: Q
 uality control\, trimming and alignmentcheck the quality of reads with Mul
 tiQCremove bad quality data with Trimmomaticinfer strandedness with RseQCa
 lign RNA-seq reads to the reference genome with HISAT2 and STARefficient a
 nalysis: how to assign paired FASTQ files to samples and align all the sam
 ples with one clickperform alignment level quality control using RseQC7.4.
 2022 at 9-12: Quantifying expression\, experiment level QC\, differential 
 expression analysisquantify expression by counting reads per genes using H
 TSeqcheck the experiment level quality with PCA plots and heatmapsanalyze 
 differential expression with DESeq2 and edgeRtake multiple factors (includ
 ing batch effects) into account in differential expression analysisproduce
  heatmaps of differentially expressed geneshow to share analysis with a co
 lleague8.4.2022 at 9-12: QuantSeq data analysisMultiQC: how to detect UMI\
 , TATA and polyA readthrough and adaptersextract UMI with UMI-toolsremove 
 polyA readthrough\, adapters and bad quality ends with BBDukalign RNA-seq 
 reads to the reference genome with STARdeduplicate alignments using UMI-to
 olsnote that in the exercises we practise the full workflow\, which includ
 es also strandedness inference\, quantitation\, experiment level QC and di
 fferential expression analysis. TrainersEija Korpelainen (CSC)\, Maria Le
 htivaara (CSC)Course materialsBefore the course you will get access to the
  course videos available in Chipster Youtube channel. Slides and exercises
  will be shared on during the course.Price 60eur
LOCATION:Online
SUMMARY:Analysis of bulk RNA-seq data using Chipster
URL;VALUE=URI:https://ssl.eventilla.com/bulkrnaseq2022
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