Statistical Methods for Functional Genomics
June 26 - July 9, 2020
Application & Materials Deadline: March 15, 2020

Instructors:

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: We are closely monitoring the COVID-19 situation as it evolves, following CDC guidelines to ensure the safety and well-being of our participants and staff. Advisory

As of March 3rd, CSHL has postponed or canceled all upcoming scientific conferences and courses bringing participants to campus through April 5th, and we are evaluating future events on a rolling basis. 

Participants from CDC Warning Level 3 countries are being advised to cancel their participation unless they can demonstrate having departed the area at least two weeks prior to their visit to CSHL. 

We anticipate making a decision about this course and communicating to all participants soon.

Travel Plans: If you have not already made travel arrangements, we would recommend holding off on that until after our decision is announced. 

Travel Insurance Tip: CSHL recommends that all participants look into the possibility of extended travel insurance, for example, Cancel for Any Reason Travel Insurance (CFAR).

*********

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

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.

Topics Include:
  • 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.

2019 Speakers:

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:
  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: