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Lecture slides for the course RNA-seq data analysis with Chipster

https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/RNA-Seq/Eija_Korpelainen/RNAseq_data_analysis_with_Chipster_2015/lectures_RNAseq_data_analysis_with_Chipster_2015.md

Lecture slides for the course RNA-seq data analysis with Chipster

Keywords

FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

Authors

Type

  • Lecture

Description

This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis. It discusses also experimental design. Material updated in Dec 2015.

Aims

Performing RNA-seq analysis, Being able to choose an appropriate strategy, Recognizing the challenges and pitfalls, Recognizing and troubleshooting issues with the data, Recognizing the importance of experimental design

Prerequisites

  • None.

Target audience

The course is suitable for any researcher interested in learning RNA-seq data analysis.

Learning objectives

  • Applying FastQC quality control software and interpreting the output
  • Deciding on trimming/filtering if preprocessing is needed. Using Trimmomatic software.
  • Differentiating genome and trancriptome alignment
  • Selecting the appropriate alignment tool
  • Recognizing the challenges and pitfalls in alignment
  • Producing alignment with TopHat2
  • Interpreting the aligner output
  • Being able to visualise alignments
  • Applying RseQC software for alignment level QC and interpreting the output
  • Producing a table of counts with HTSeq software
  • Identifying confounding effects with PCA and MDS plots and taking necessary action
  • Recognizing the need for normalization
  • Performing DE analysis with edgeR and DESeq2 and interpreting the output
  • Understanding and performing multifactor analysis
  • Operating Chipster software
  • Designing experiments properly

Materials

  • Slides for lectures on RNA-seq data analysis

Data

  • Not applicable.

Timing

The lecture and practicals can be performed in one day.

Content stability

The content is updated approximately every 3 months.

Technical requirements

  • Not applicable.

Literature references

  • Suitable reading includes the book RNA-seq data analysis - practical approach

Keywords: FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

Additional information

Authors: Eija Korpelainen @eija, ekorpelainen@gmail.com