Over the last decade, massively parallel DNA sequencing has markedly impacted the practice of modern biology and is being utilized in the practice of medicine. The constant improvement of these platforms means that costs and data generation timelines have been reduced by orders of magnitude, facilitating investigators to conceptualize and perform sequencing-based projects that heretofore were time-, cost-, and sample number-prohibitive. Furthermore, the application of these technologies to answer questions previously not experimentally approachable is broadening their impact and application. However, data analysis remains a complex and often vexing challenge, especially as data volumes increase.
This intensive two week course will explore use and applications of massively parallel sequencing technologies, with a focus on data analysis and bioinformatics. Students will be instructed in the detailed operation of several platforms, including library construction procedures, general data processing, and in-depth data analysis. A diverse range of the types of biological questions enabled by massively parallel sequencing technologies will be explored including DNA re-sequencing of known cancer genes, de novo DNA sequencing and assembly of genomes, RNA-sequencing, and others that are tailored to the student's research areas of interest.
Cloud-based computing will also be explored. Guest lecturers will highlight unique applications of these disruptive technologies.
We encourage applicants from a diversity of scientific backgrounds including molecular evolution, development, neuroscience, medicine, cancer, plant biology and microbiology.
Ken Dewar, McGill University & Genome QC Innovation Centre
Olivier Elemento, Weill Cornell Medical College
Jeremy Goecks, OHSU
Brian Haas, Broad Institute
Michael Hoffman, University of Toronto
Tuuli Lappalainen, New York Genome Center
Christopher Maher, Washington University School of Medicine
Gabor Marth, University of Utah
Karyn Meltz Steinberg, Washington University
Maria Nattestad, DNA Nexus
Jonathan Preall, Cold Spring Harbor Laboratory
Nikolaus Schultz, Memorial Sloan Kettering Cancer Center
Fritz Sedlazeck, Baylor College of Medicine
Michael Zody, New York Genome Center
Major support provided by: National Human Genome Research Institute.
Access to cloud computational resources may be supported by an AWS in Education Grant award from Amazon.
Stipends are available to offset tuition costs as follows:
Please indicate your eligibility for funding in your stipend request submitted when you apply to the course. Stipend requests do not affect selection decisions made by the instructors.
Cost (including board and lodging): $3,960
No fees are due until you have completed the full application process and are accepted into the course. Students accepted into the course should plan to arrive by early evening on November 4 and plan to depart in the morning of November 17.
Before applying, ensure you have:
- Personal statement/essay;
- Letter(s) of recommendation;
- Curriculum vitae/resume (optional);
- Financial aid request (optional).
If you are not ready to fully apply but wish to express interest in applying, receive a reminder two weeks prior to the deadline, and tell us about your financial aid requirements, click below: