Advanced Sequencing Technologies & Bioinformatics Analysis
November 3 - 15, 2020
Application Deadline: July 31, 2020
Instructors:
- Obi Griffith, Washington University School of Medicine
- Malachi Griffith, Washington University School of Medicine
- Elaine Mardis, Nationwide Children's Hospital Research Institute
- W. Richard McCombie, Cold Spring Harbor Laboratory
- Aaron Quinlan, University of Utah
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 (Illumina, PacBio, Nanopore, Etc.), including library construction procedures, general data processing, and in-depth data analysis. Students will be introduced to Unix command-line, important file formats, alignment, data visualization, basic scripting in R, bash and other program languages, cluster job submission and bioinformatics pipeline development. A diverse range of the types of biological questions enabled by massively parallel sequencing technologies will be explored such as bulk transcriptome profiling (RNAseq), single-cell transcriptome/proteome profiling (scRNAseq, CITEseq), epigenome profiling (ATAC-seq), small variant discovery and interpretation, structural variant discovery, long read applications, probability and statistics for genomics analysis, 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.
Cost (including board and lodging): $4,080
Stipends are available to offset tuition costs.
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 2 and plan to depart in the morning of November 15.
Before applying, ensure you have:
- Personal statement/essay;
- Letter(s) of recommendation;
- Curriculum vitae/resume (optional);
- Financial aid request (optional).
