Advanced Sequencing Technologies & Bioinformatics Analysis
November 11 - 19, 2021  (Virtual)
Application Deadline: Closed


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


See the roll of honor - who's taken the course in the past

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 condensed seven day virtual course (Nov 11,12,15,16,17,18,19) will explore use and applications of massively parallel sequencing technologies, with a focus on data analysis and bioinformatics. Formal lectures and discussion will likely be held morning (10am-1pm) and afternoons (2pm-5pm) (US east coast time) to allow participation of students from North America and Europe. 

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. Given the condensed curriculum, several types of biological questions enabled by massively parallel sequencing technologies will be explored including bulk transcriptome profiling, single-cell transcriptome profiling and small variant discovery/interpretation, and other approaches 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.

2020 Guest Lecturers (2021 guest lecturers to be announced shortly)

Aravinda Chakravarti, NYU School of Medicine
Emily Hodges, Vanderbilt University School of Medicine
Caleb Lareau, Harvard University
Gabor Marth, University of Utah
Robert Martienssen, Cold Spring Harbor Laboratory/HHMI
Karen Miga, UCSC Genomics Institute
Allegra Petti, Washington University School of Medicine
Peter Scacheri, Case Western Reserve University
Adam Siepel, Cold Spring Harbor Laboratory
Peter Smibert, New York Genome Center
Jan Witkowski, Cold Spring Harbor Laboratory

Support & Stipends

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.


Virtual Attendance: $700

Virtual Attendance packages include registration, access to online Zoom-based oral sessions, a dedicated Slack channel and access to the video archive on the Leading Strand for ~six weeks following the Course.

Before applying, ensure you have:
Before applying, ensure you have:
  1. Personal statement/essay;
  2. Letter(s) of recommendation;
  3. Curriculum vitae/resume (optional);
  4. Financial aid request (optional).
    More details.

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: