Attention

There is a new revised release, using data from E. coli to speed the analysis steps up. The new tutorial can be accessed at https://genomics.sschmeier.com/.

Computational Genomics Tutorial

This is an introductory tutorial for learning computational genomics mostly on the Linux command-line. You will learn how to analyse next-generation sequencing (NGS) data. The data you will be using is real research data. The final aim is to identify genome variations in evolved lines of wild yeast that can explain the observed biological phenotypes. Until 2020, Sebastian was teaching this material in the Massey University course Genome Science.

More information about other bioinformatics material and our past research can be found on the former webpages of the Schmeier Group (https://www.schmeierlab.com).

Note

A PDF-version of this tutorial can be downloaded here.

Contents

• 1. Introduction
  • 1.1. The workflow
  • 1.2. Learning outcomes
• 2. Tool installation
  • 2.1. Install the conda package manager
  • 2.2. Create environments
  • 2.3. Install software
  • 2.4. General conda commands
• 3. Quality control
  • 3.1. Preface
  • 3.2. Overview
  • 3.3. Learning outcomes
  • 3.4. The data
  • 3.5. The fastq file format
  • 3.6. The QC process
  • 3.7. PhiX genome
  • 3.8. Adapter trimming
  • 3.9. Sickle for dynamic trimming
  • 3.10. Quality assessment of sequencing reads (FastQC)
• 4. Genome assembly
  • 4.1. Preface
  • 4.2. Overview
  • 4.3. Learning outcomes
  • 4.4. Before we start
  • 4.5. Creating a genome assembly
  • 4.6. Assembly quality assessment
  • 4.7. Compare the untrimmed data
  • 4.8. Assemblathon
  • 4.9. Further reading
  • 4.10. Web links
• 5. Read mapping
  • 5.1. Preface
  • 5.2. Overview
  • 5.3. Learning outcomes
  • 5.4. Before we start
  • 5.5. Mapping sequence reads to a reference genome
  • 5.6. BWA
  • 5.7. Bowtie2 (alternative to BWA)
  • 5.8. The sam mapping file-format
  • 5.9. Mapping post-processing
  • 5.10. Mapping statistics
  • 5.11. Sub-selecting reads
• 6. Taxonomic investigation
  • 6.1. Preface
  • 6.2. Overview
  • 6.3. Before we start
  • 6.4. Kraken2
  • 6.5. Centrifuge
  • 6.6. Visualisation (Krona)
• 7. Variant calling
  • 7.1. Preface
  • 7.2. Overview
  • 7.3. Learning outcomes
  • 7.4. Before we start
  • 7.5. Installing necessary software
  • 7.6. Preprocessing
  • 7.7. Calling variants
  • 7.8. Post-processing
• 8. Genome annotation
  • 8.1. Preface
  • 8.2. Overview
  • 8.3. Learning outcomes
  • 8.4. Before we start
  • 8.5. Installing the software
  • 8.6. Assessment of orthologue presence and absence
  • 8.7. Annotation
  • 8.8. Interactive viewing
  • 8.9. Installing IGV
  • 8.10. Assessment of orthologue presence and absence (2)
• 9. Orthology and Phylogeny
  • 9.1. Preface
  • 9.2. Learning outcomes
  • 9.3. Before we start
  • 9.4. Installing the software
  • 9.5. Finding orthologues using BLAST
  • 9.6. Performing an alignment
  • 9.7. Building a phylogeny
  • 9.8. Visualizing the phylogeny
• 10. Variants-of-interest
  • 10.1. Preface
  • 10.2. Overview
  • 10.3. Learning outcomes
  • 10.4. Before we start
  • 10.5. General comments for identifying variants-of-interest
  • 10.6. SnpEff
• 11. Quick command reference
  • 11.1. Shell commands
  • 11.2. General conda commands
• 12. Coding solutions
  • 12.1. QC
  • 12.2. Assembly
  • 12.3. Mapping
• 13. Downloads
  • 13.1. Tools
  • 13.2. Data
  • 13.3. Tutorial