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Guide to RNA-seq Analysis
  • Introduction
  • Preparations
    • Work environment
    • Softwares and databases
    • Obtain sequencing data
    • R packages
  • Raw read processing
    • QC & trimming
    • Mapping & quantification
      • Alignment-free method
      • Alignment-based method
  • Differential expression analysis in R
    • Building a TxDb object
    • About tximport
    • Convert Salmon output to Sleuth-compatible format
    • Differential gene expression (DGE) analysis using DESeq2
      • DGE analysis with Salmon/Kallisto input
      • DGE analysis with STAR input
      • DGE analysis with STAR + RSEM input
    • Differential transcript expression (DTE) analysis using DESeq2
      • DTE analysis with Salmon/Kallisto input
      • DTE analysis with STAR + RSEM input
    • DGE and DTE analysis of Salmon/Kallisto inputs using Sleuth
    • Differential transcript usage (DTU) analysis
      • DTU analysis using DRIMSeq
      • DTU analysis using DEXSeq
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Introduction

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Guide to RNA-seq Data Analysis

I-Hsuan Lin

The University of Manchester

RNA-seq utilizes the sequencing technology to assay the presence and quantity of RNA molecules in the given sample. RNA-seq offers many advantages and supersede the microarray technology that was introduced in 2000s. This includes detects known and novel transcripts, increased specificity and sensitivity, and identification of low-abundance transcripts and isoforms with sufficient sequencing depth. RNA-seq has also been used to discover alternative splicing variants, chimeric RNAs result from fusion genes and RNA editing sites. We can compare RNA-seq data between conditions to detect differences across groups of samples in terms of (1) gene-level expression, (2) transcript/isoform-level expression, and (3) transcript/isoform usage within a gene.

I will use a real-world illumina paired-end RNA sequencing dataset to demonstrate a step-by-step guide where readers can reproduced the analysis. The complete workflow includes:

  • Performing QC and trimming to pre-process RNA-seq raw data

  • Mapping of trimmed reads using either alignment-free (Salmon) and alignment-based (STAR) methods

  • Quantifing gene and transcript expression

  • Performing statistical testing to identified differentially expressed genes, transcripts and also detected expression switching between transcripts

License

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