Workshop: Introductory Population Genomics: from Data to Inference
Monday 8th to Friday 12th May 2017, Berlin (Germany) http://www.physalia-courses.org/courses/course9/
Instructors:
- Dr. Martin Taylor (http://www.physalia-courses.org/instructors/t9/)
- Dr. Lewis Spurgin (http://www.physalia-courses.org/instructors/t8/)
Overview:
Next generation sequencing has revolutionized evolutionary biology allowing unprecedented resolution and insight into evolutionary questions that appeared intractable only a few years ago. The course will cover the basics of population genomic analysis from SNP data onwards and will cover the key analyses that may be required to successfully analyze a population genetic data set. The course will NOT cover steps prior to generation of a .vcf file or SNP data set such as NGS data demultiplexing, clustering and SNP calling (This is covered in detail in the Introduction to RADseq course). This course will introduce Linux and the command line environment, basic perl and python usage, file conversions and manipulation, population structure and differentiation in R, outlier analysis, landscape / seascape genomics and introgression. Having completed the course, students should have a good understanding of the software and methods available for population genomic analysis and be competent in population genomic analysis.
Intended audience & assumed background:
This workshop is aimed at postgraduate students and early career researchers who are interested in using population genomic tools in their research. No previous experience of bioinformatics is required, but an underpinning in evolutionary biology and basic population genetics concepts such as Hardy Weinberg Equilibrium and FST are desirable. The course will use a range of software including the Linux operating system and R.
Teaching format:
The workshop is delivered over ten half-day sessions (see the detailed curriculum below). Each session consists of a combination of lectures and practical exercises, with breaks at the organisers’ discretion. There will also be time for students to discuss their own problems and data.
Curriculum:
Monday 8th - Classes from 9:30 to 17:30
Session 1 - Introduction to Linux and the command line (Dr. Martin Taylor)
- Installation of required software
- Introduction to linux operating system
- Working on the command line. Basic bash shell commands and navigation.
- Introduction to Perl and Python
Session 2 - Understanding genomic data formats (Dr. Martin Taylor)
- Understanding and working with VCF files using VCF tools
- Data conversion and manipulation using Plink
- Text editors
Tuesday 9th-Classes from 9:30 to 17:30
Session 3- Introduction to genetic analysis in R (Dr. Lewis Spurgin)
- Introduction to R
- Reading data into R
- Data manipulation in R
- Introduction to Adegenet and other genetics packages
Session 4 - Genomic diversity estimation (Dr. Lewis Spurgin)
- Estimating heterozygosity and nucleotide diversity
- Hardy Weinberg
- Linkage disequilibrium
- Introduction to ggplot2
Wednesday 10th-Classes from 9:30 to 17:30
Session 5 - Population structure and differentiation (Dr. Martin Taylor & Dr. Lewis Spurgin)
- Estimating and understanding FST
- Visualising genetic structure using MDS and PCA
- STRUCTURE and related software
- Estimating migration
Session 6 - Identifying selection within populations (Dr Lewis Spurgin)
- Marker-based genetic diversity
- Introduction to sliding windows
- Tajima’s D and related statistics
- Introduction to GO analyses
Thursday 11th - Classes from 9:30 to 17:30
Session 7 - Identifying selection among populations (Dr. Lewis Spurgin)
- FST outlier analysis
- EigenGWAS
Session 8 - Incorporating landscape and seascape into population genomics (Dr. Martin Taylor)
- Seascape / landscape genetics
- Environmental / genomic correlation
Friday 12th-Classes from 9:30 to 17:30
Session 9 - Hybridisation and introgression (Dr. Martin Taylor)
- Identifying hybrids and introgression using genotype data
Session 10 - Summary data troubleshooting session (Dr Martin Taylor & Dr Lewis Spurgin)
- Time to answer questions on any areas covered during week.
- Talk to us about your own data
Application deadline: April 14th 2017.
Please feel free to contact us if you need any further information.
