The need for phylogenetic comparisons of molecular sequences has been increasing steadily with the explosive growth of genomic sequence data.  Estimation of species phylogenies and species divergence times, inference of population demographic processes and migration patterns, and delineation of species boundaries are central to our understanding of biodiversity and to interpreting genomic sequence data. 

Furthermore, molecular evolutionary analyses can provide important insights into the evolutionary process of sequences and genes: for example, detecting adaptive molecular evolution may be useful to disentangle viral infections and dynamics.  These processes can be analyzed via sophisticated statistical inference methods by means of efficient  algorithms that are implemented in a plethora of software packages.  However, empirical biologists often find it challenging to make effective use of those computational tools, partly due to the challenges in understanding their underlying statistical and computational principles.

Run biennially at the Genome Campus (and jointly with EMBL-EBI) this hands-on computational course aims to provide early-career stage researchers with the theoretical knowledge and practical skills to carry out molecular evolutionary analyses on sequence data.  The extensive programme comprises a mixture of lectures and computer practicals, and covers: data retrieval and assembly, alignment techniques, phylogeny reconstruction methods including maximum likelihood and Bayesian methods, hypothesis testing, and coalescent-based inference methods at the interface of phylogenetics and population genetics.  Besides acquiring the skills to properly deploy major software packages such as PhyML, RaXML, MrBayes, BEAST, BPP, etc., the course also focuses on statistical inference methods and algorithms. This will allow the participants to attain a thorough understanding of the underlying principles of the software they use.  

The course will also offer a unique opportunity for the participants to interact with some of the world-leading scientists and authors of famous software packages in evolutionary bioinformatics, including Nick Goldman, Tracy Heath, Brian Moore, Adam Leache, Bruce Rannala, Benjamin Redelings, Alexandros Stamatakis, Tanja Stadler, Jeff Thorne, and Ziheng Yang.

Target audience
The course is aimed primarily at biology and bioinformatics PhD students or postdocs in the early stages of their research career, and who already have some familiarity with phylogenetic methods (i.e., have already used some of the computer programs).  Programming experience is not required, although knowledge of R and experience in a scripting language such as python or perl will be very useful.  Candidates without prior experience with the Unix/Linux command line will be required to acquire these skills prior to the course. Training materials and exercises for improving Unix/Linux skills of participants will be provided before the course.

Feedback from the 2015 course

• "Thank you for the excellent course!"
• "Thank you for a fantastic and informative two weeks!!!"
• "This course was very inspirational and i learned very many new skills here. I will use the software that was introduced during the course in my work. I found the all the Insturctors and TI-s very professional and easy to access. I also found the participants being from very different fields to be very enriching and i found many potential collaborators from the course."
• "Thank you!!! Keep up the good work! The difference you make in our careers as early researchers cannot be stressed enough."
• "Just keep offering the course, I think that what you are doing here is an incredibly valuable service to the community!"
• "The instructors and teaching assistants were all a high point of the course. They were friendly, understanding and approachable"
  

The programme will include lecture and practical computer-based sessions covering the following topics:

• Data retrieval and assembly
• Next Generation Sequencing (NGS) technologies*
• Alignment techniques
• Phylogeny reconstruction
• Statistical tests of phylogenetic hypotheses
• Detection of molecular adaptation
• Molecular clock dating integrating fossil and morphological evidence
• Species tree estimation and species delimitation under the multispecies coalescent model
• Parallel computing

*Please note: The course focuses on NGS analyses for molecular evolution and does not include tutorials on the traditional DNA-seq or RNA-seq data processing (QC, read mapping, SNP calling, expression analysis, assembly etc).

Additional sessions
There will also be the opportunity for a limited number of participants with programming experience in bioinformatics to participate in 2–3 ‘hands-on’ coding sessions led by the course instructors.

Learning outcomes
The overall aim is to enable participants to critically review, assess and apply quantitative computational methods for evolutionary data analyses.

By the end of the course participants should be able to:

• Interpret evolutionary trees and recognise / discuss the power of molecular phylogenies for understanding real-world biological questions, relating to evolutionary history, current-day biodiversity and future diversification of living organisms
• Browse, query and extract genome sequence from public databases, and create multiple sequence alignments.
• Employ appropriate bioinformatics skills that also allow for the analysis of large genome-scale datasets, including command line use of specialist software, simple scripting, compiling programs and submitting jobs on multi-core servers and compute clusters. 
• Select and apply appropriate commonly used phylogenetic software packages (such as PhyML, RAxML, PAML, MrBayes, BEAST) to infer phylogenetic trees, estimate divergence times, and test phylogenetic hypotheses.
• Understand and explain the underlying principles of major phylogenetic methods such as distance matrix-based, maximum likelihood, and Bayesian methods, including the MCMC method. 
• Understand and explain the use of Markov models of nucleotide, amino acid and codon substitution, hypothesis testing using the likelihood ratio test, coalescent and multispecies coalescent models in species tree estimation and species delimitation.
• Apply likelihood ratio tests to infer the existence and location of molecular adaptation affecting protein-coding genes.
  

Prerequisites
The course is aimed primarily at biology and bioinformatics PhD students or postdocs in the early stages of their research career, and who already have some familiarity with phylogenetic methods (i.e., have already used some of the computer programs).  Programming experience is not required, although knowledge of R and experience in a scripting language such as python or perl will be very useful.  Candidates without prior experience with the Unix/Linux command line will be required to acquire these skills prior to the course. Training materials and exercises for improving Unix/Linux skills of participants will be provided before the course.

Cost
The course is subsidised by the Wellcome Genome Campus Advanced Courses and Scientific Conferences Programme. This is a residential course and there is a fee of £1660 towards board and lodging for non-commercial applicants. Please contact us for the commercial fee.

Additional limited bursaries are available (up to 50% of the course fee) and are awarded on merit. Please see the "Bursaries" tab for details.

Applications
Applications for this course can be completed online. If you have any problems with the online application process, please contact us.

Please note: Applications must be supported by a recommendation from a scientific or clinical sponsor (e.g. supervisor or head of department). A request for a supporting statement will be sent to your nominated sponsor automatically during the application process. Applicants must ensure that their sponsor provides this supporting statement by the application deadline. Applications without a supporting statement cannot be considered.

Deadlines
Deadline for Applications: Closed

Travel visas
Please contact the event organiser if you require a letter to support a travel visa application. Note that letters will be provided to confirmed attendees.

Non-European Economic Area or Swiss nationals may be required to have a visa to enter the UK.
Early application is strongly advised, as this process can take 6-8 weeks or longer.

Please visit the following websites for further information:
UK Border Agency website and information for general visitors and business visitors.

Cost
The course is subsidised by the Wellcome Genome Campus Advanced Courses and Scientific Conferences Programme. This is a residential course and there is a fee of £1660 towards board and lodging for non-commercial applicants. Please contact us for the commercial fee.

Bursaries
Advanced Courses are subsidised for non-commercial applicants from anywhere in the world. Additional, limited bursaries are available (up to 50% of the course fee) and are awarded on merit. If you would like to apply for a bursary, please complete the bursary section of the online application form.

Please note that both the applicant and sponsor are required to provide a justification for the bursary as part of the application.

Bursary terms and conditions

UK Courses (held at the Wellcome Genome Campus, Hinxton, Cambridge)
A limited number of bursaries are available for each course. These are awarded by the selection committee according to merit. The bursary covers a maximum of 50% of the course fee, though in exceptional circumstances an application for the total course fee may be considered. Where there are many bursary applications, the selection committee may issue smaller amounts. We cannot assist with travel costs to attend UK courses.

Overseas Courses (held outside of the UK)
A limited number of bursaries are available for each course. These are awarded on merit to cover travel, accommodation and sustenance. The maximum award for travel (economy class) will be £750.

Bursaries can be applied for as part of the course application form. Applicants will be notified of a bursary award along with their place on the course, usually within one month of the application deadline. The decision of the selection committee is final.