The advancement of high-throughput sequencing (HTS) technologies and the rapid development of numerous
analysis algorithms and pipelines in this field has resulted in an unprecedentedly high demand for training
scientists in HTS data analysis.
Embarking on developing new training materials is challenging for many reasons; often trainers do not have prior experience in preparing or delivering such materials and if they do, they frequently struggle to keep them up to date.
To support trainers in materials preparation, reduce the duplication of effort by increasing the re-use of existing materials, and allow for the sharing of teaching experience among the HTS trainers community, we created a repository of curated HTS training materials.
During the “Best practices in next-generation sequencing data analysis” workshop held in Cambridge UK, in January 2015, as a consortium of 29 teachers, we have developed a strategy for materials’ curation and dissemination. This resulted in standards for describing training materials and in the establishment of the repository you are currently browsing.
The devised standards have been applied to the curation of existing materials contributed by members of the trainers' consortium. The repository has been implemented using Git, hence it is decentralized and self-managed by the community and can be forked/built-upon by all users.
This resulted in standards for describing training materials and in the establishment this repository which allows trainers to access annotated materials that can now be re-used, modified or incorporated into new courses.
RNA-Seq pipeline from initial quality control, data trimming to alignment, feature summarization and downstream differential expression analysis.
ChIP-Seq pipeline from initial quality control, alignment, peak calling, to genomic annotation and differential binding analyses.
Variant analysis pipeline from initial quality control, to alignment, variant calling and population level analyses.
Understand sequencing technologies and common data formats.
Fundamentals for working with HTS data include statistical knowledge and familiarity with a Linux envirnoment as well as programming languages such as R or Python.
If you are missing your favorite module, get in touch with us! Looking forward to helping uploading new topics.
git clone https://microasp.upsc.se/ngs_trainers/Materials.git
Bastian Schiffthaler et al., PLOS Computational Biology, 2016
|First Name||Last Name||Institute / Company||Country||Elixir member||Goblet member|
|Andrew||Warry||University of Nottingham (ADAC)||UK|
|Anna||Poetsch||Francis Crick Institute/ Okinawa Institute of Science and Technology||UK/ Japan|
|Anton||Enright||EMBL - EBI||UK|
|Bastian||Schiffthaler||UPSC Umeå, dept. of Plant Physiology||Sweden|
|Bert||Overduin||Edinburgh Genomics / The University of Edinburgh||UK|
|Charlotte||Soneson||Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics||Switzerland||x||x|
|Chiara||Batini||University of Leicester||UK|
|David||Sims||CGAT, MRC FGU, Oxford||UK|
|Eija||Korpelainen||CSC - IT Center for Science||Finland||x||x|
|Gabriella||Rustici||University of Cambridge||UK||x||x|
|Hedi||Peterson||University of Tartu||Estonia||x|
|Jenny||Drnevich||HPCBio & Carver Biotechnology Center, University of Illinois||USA|
|Kate||Lee||University of Leicester||UK|
|Mark||Dunning||Cancer Research UK, Cambridge Institute||UK|
|Mark||Fernandes||Institute of Food Research||UK|
|Martijn||Herber||Hanze University of Applied Science||NL|
|Matthew||Blades||University of Leicester||UK|
|Nicolas||Delhomme||Umeå Plant Science Center||Sweden|
|Priit||Adler||University of Tartu||Estonia||x|
|Radhika||Khetani||Harvard School of Public Health||USA|
|Suraj||Menon||University of Cambridge||UK|