Statistical Methods for Functional Genomics (CANCELED)
June 26 - July 9, 2020
Application & Materials Deadline: March 15, 2020
Vince Carey, Harvard University
Sean Davis, National Institute of Health
Keegan Korthauer, University of British Columbia, Canada
Michael Love, University of North Carolina, Chapel Hill
Tomas Rube, University of California Merced
COVID-19: UPDATE April 1, 2020: It is with considerable regret that we announce the cancellation of this course for 2020 but it will be rescheduled to similar dates in 2021.
Over the past decade, high-throughput assays have become pervasive in biological research due to both rapid technological advances and decreases in overall cost. To properly analyze the large data sets generated by such assays and thus make meaningful biological inferences, both experimental and computational biologists must understand the fundamental statistical principles underlying analysis methods. This course is designed to build competence in statistical methods for analyzing high-throughput data in genomics and molecular biology.
- The R environment for statistical computing and graphics
- Introduction to Bioconductor
- Review of basic statistical theory and hypothesis testing
- Experimental design, quality control, and normalization
- High-throughput sequencing technologies
- Expression profiling using RNA-Seq and microarrays
- In vivo protein binding using ChIP-Seq
- High-resolution chromatin footprinting using DNase-Seq
- DNA methylation profiling analysis
- Integrative analysis of data from parallel assays
- Representations of DNA binding specificity and motif discovery algorithms
- Predictive modeling of gene regulatory networks using machine learning
- Analysis of posttranscriptional regulation, RNA binding proteins, and microRNAs
Format: Detailed lectures and presentations by instructors and guest speakers will be combined with hands-on computer tutorials. The methods covered in the lectures will be applied to example high-throughput data sets.
Brittany Adamson, Princeton University, Princeton, NJ
Elana Fertig, Johns Hopkins University, Baltimore, MD
Tuuli Lappalainen, New York Genome Center & Columbia University, New York, NY
Karen Mohlke, University of North Carolina, Chapel Hill, NC
Robert Patro, Stony Brook University, Stony Brook, NY
This course is supported with funds provided: National Institute of General Medical Sciences.
Support & Stipends:
On average, 50% of trainees receive financial support on a needs-basis.
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): $4,080
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 June 25 and plan to depart after lunch on July 9.
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: