RNA Transcriptomics19 - 28 June 2019Wellcome Genome Campus, UK
Deadlines (at 23:59 UTC):
- Application and bursary deadline Closed
Hands-on training in the latest laboratory and computational methods for transcriptomic analysis.
Rapid advances in genome analysis technology have opened up new and exciting possibilities for studying the transcriptome and its function.
In particular, third generation, single molecule sequencing technologies and single cell technologies, combined with perturbation tools, allow the analysis of complete RNA species – both short and long – at high resolution. In parallel, these tools have opened new ways in understanding gene functions at the tissue, network and pathway level, as well as detailed characterization of their function.
This exciting course will provide hands-on training in advanced laboratory and computational methodologies for the analysis of transcriptomes, including long non-coding RNAs and microRNAs, along with their post-transcriptional and epi-transcriptomic modification.
The programme will focus on new technologies for direct RNA sequencing, and complete single molecule cDNA sequencing, single cell RNA sequencing and the characterisation and analysis of non-coding RNAs (such as lncRNAs and microRNAs). Analysis of the epi-transcriptome, including RNA methylation and modification, will also be covered.
The practical programme will be complemented by distinguished guest speakers, who will present the latest research in this fast-moving field, along with opportunities for informal discussions.
The course will include laboratory and computational* practical sessions, along with lectures and discussions, covering the following topics:
- Overview of single molecule long read sequencing technologies
- Full length total RNA sequencing
- Full length cDNA sequencing
- Small RNA sequencing
- Single cell transcriptome data generation and analysis
- Identification of post-transcriptional modifications in RNA (epi-transcriptomics)
- Functional assays for lncRNA biology
- Integration of microRNA and mRNA data; functional analysis of microRNAs
- Expression network and pathway integration and analysis
After attending this course, participants should be able to:
- Evaluate advanced RNA transcriptomic analysis methodologies and their applications
- Appreciate different approaches currently in use to address specific research questions in the field
- Assess the strengths, weaknesses and limitations of different methodologies and approaches
- Integrate and apply the knowledge and training from the course to their own research interests
*To fully benefit from the data analysis sessions participants will require a basic knowledge of Linux/Unix command line as well as the R programming environment. Numerous free online tutorials are available in these resources. e.g.:
- Instructors and speakers
McGill University, Canada
University of Oxford, UK
Curie Institute, France
University of Cambridge, UK
- Cost and bursaries
Cost Accommodation / meals *Course fee £1150 This is a residential course and the fee includes all accommodation and meals.
*The course fee is subsidised by Wellcome Genome Campus Advanced Courses and Scientific Conferences and applies to non-commercial applicants. Please contact us for the commercial fee.
Limited bursaries are available (up to 50% reduction on 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.
Where there are many bursary applications, the selection committee may issue smaller amounts.
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.
Please note that both the applicant and sponsor are required to provide a justification for the bursary as part of the application.
Additional funding opportunities
Visit our support page for additional financial support currently available.
Accommodation services phishing scam – please be vigilant. More information.
- How to apply
Applicants should be researchers or clinician scientists interested in applying advanced laboratory and computational methodologies for the analysis of transcriptomes, including long non-coding RNAs and microRNAs, as well as their post-transcriptional and epi-transcriptomic modification. It is suitable for PhD students working on a relevant project, postdoctoral trainees and fellows, as well as early career researchers.
To fully benefit from the data analysis sessions participants will require a basic knowledge of Linux/Unix command line as well as the R programming environment. Numerous free online tutorials are available for these resources. e.g.:
How to Apply
Please complete the online application form. Places are limited and will be awarded on merit. 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, line manager 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.
Successful applicants will be provided with a support letter for their visa application, if required.
Please visit the following websites for further information on visiting the UK:
Feedback from the inaugural 2018 course:
“Excellent instructors, very inspiring, simply Many thanks.”
“The course was exactly as advertised and even exceeded all my expectations. I had no idea before this course about which techniques to use for my project task related with transcriptomics. Now, I am feeling completely confortable to perform my study correctly.”
“Thank you all for putting on such an excellent course! I think this is the best scientific course I have ever been on. My main aim was to learn RNA-seq bioinformatics and I now feel I can give it a good go! I had never used R or the command line for any serious work before and this was an excellent introduction. It was also great to meet all the other participants from around the world!”
“I would like to thank all the instructors and my co-participants for a rewarding ten days.”
“I am very happy and grateful that I was selected to participate in this course. Thank you.”