Introduction

Overview

Teaching: 10 min
Exercises: 0 min

Questions

• What are the goals of this practical training?

• What data do we work on?

Objectives

• Describe the goals of this practical training.

• Describe the characteristics of the isolates.

The lessons of the first two days introduce and reinforce basic skills in the Unix shell and R, and are designed for learners with no programming experience. The general topics and skills covered include:

Interacting with Computers

• Could Computing
• Connecting to remote computing (SSH/PuTTY)
• File Transfer (FileZilla, other command-line tools: scp, rsynch, wget, etc. )

Data Management and Organization

• Open source
• Metadata and reproducibility
• Important genomics file formats (CSV/TSV, FastQ, SAM/BAM, VCF, etc.)
• Organizing a filesystem for computational projects (Linux)
• Unix Shell (command-line: ls, cd, mkdir, cp, rm, wc, grep, cut, columns, head, tail, less etc,)
• R: Creating projects, scripts, and examining data

Data Cleaning and visualization

• R: various packages and functions
• R: dplyr
• R: ggplot
• FastQC - quality control of high-throughput sequence data
• Seqtk - filtering and trimming of high-throughput sequence data
• Integrated Genome Viewer

Automation and scripting

• R scripting
• ‘For’ loops
• Building automated pipelines
• Using multithreaded applications

Overview of our Data Set and Narrative

Microbes are ideal organisms for exploring ‘Long-term Evolution Experiments’ (LTEEs) - thousands of generations can be generated and stored in a way that would be virtually impossible for more complex eukaryotic systems. In Lenski et.al., 12 populations of Escherichia coli were propagated for more than 40,000 generations in a glucose-limited minimal medium. This medium was supplemented with citrate which E. coli cannot metabolize in the aerobic conditions of the experiment. Sequencing of the populations at regular time points reveals that spontaneous citrate-using mutants (Cit+) appeared in a population of E.coli (designated Ara-3) at around 31,000 generations. It should be noted that spontaneous Cit+ mutants are extraordinarily rare - inability to metabolize citrate is one of the defining characters of the E. coli species. Eventually, Cit+ mutants became the dominate population as the experimental growth medium contained a high concentration of citrate relative to glucose.

Why we chose this data set

• Simple, but iconic NGS-problem: Examine a population where we want to characterize changes in sequence a priori
• Dataset publicly available - in this case through the NCBI Sequence Read Archive (http://www.ncbi.nlm.nih.gov/sra)
• Small file sizes - while several of related files may still be hundreds of MBs, overall we will be able to get through more quickly then if we worked with a larger eukaryotic genome

Key Points

• After the first two days you will have some familiarity with working on the command line, data management, cleaning and visualization, automation and scripting