Day 2 - RNA-Seq Analysis

Day 2 - RNA-Seq Analysis

Keywords

Alignment, BAM, FASTA, FASTQ, QC, Exploratory-analysis, Feature-summarisation, Pre-processing

Authors

Type

  • Both

Description

Day 2 continues throught the steps in a typical RNA-Seq experiment from alignment to sample QC and count normalization, including a brief overview of the IGV Genome Browser.

Aims

This day aims to details the considerations of alignment to a genome and/or transcriptome, visualizing the alignments in a genome browswer, summarizing counts at the gene/transcript/exon level, and using Bioconductor packages for sample QC and normalization.

Prerequisites

  • Basic UNIX and how to submit jobs to a computing cluster
  • Basic knowledge of R
  • All the information in Day 1, but not the practical outputs

Target audience

Graduates students/post docs/beginning faculty

Learning objectives

  • Be able to decide when to align to a genome or transcriptome
  • Be able to describe the different "levels" of a gene feature and how to generate counts at each level
  • Be able to follow and modify UNIX scripts for alignment and count generation, and R scripts for QC and normalization

Materials

  • Lecture on alignment, IGV and count generation
  • Review of GFF file format
  • Lecture on QC and normalization
  • How to track sample reads at each step

Data

  • All data needed to run Day 2 practicals

Timing

6 hours contact time; practicals intersperced with lectures; easily can fit into 1 day + lunch and breaks

Content stability

Should be stable

Technical requirements

  • UNIX server with STAR >= 2.4.0i, and subread >= 1.4.6-p1. Also IGV >= 2.3 and R >= 3.1.3 on any OS.

Literature references

Keywords: Alignment, BAM, FASTA, FASTQ, QC, Exploratory-analysis, Feature-summarisation, Pre-processing

Authors: Jenny Drnevich @jenny, Radhika Khetani @radhika, Jessica Kirkpatrick krkptrc2@illinois.edu

Day 2 - RNA-Seq Analysis https://tess.elixir-europe.org/materials/day-2-rna-seq-analysis Day 2 continues throught the steps in a typical RNA-Seq experiment from alignment to sample QC and count normalization, including a brief overview of the IGV Genome Browser. Alignment, BAM, FASTA, FASTQ, QC, Exploratory-analysis, Feature-summarisation, Pre-processing