Course FAQ

There will be a mixture of lectures, coding practice and hands-on data analysis sessions, as well as office hours with teaching assistants. The first week of the course will cover preparatory material (e.g., fundamentals of bioinformatics, computational biology, cancer immunology, statistics, computing and programming). The second week will focus on analysis of whole-exome DNA-Seq data: germline and somatic variant calling and annotation, HLA-typing, neo-epitope prediction.

Week 1 Topics

  • Introduction to RStudio
  • Computing Environment
  • Introduction to Reproducible Analysis I
  • Introduction to Reproducible Analysis II
  • Mechanics of High Throughput Sequencing Technology I
  • Mechanics of High Throughput Sequencing Technology II 
  • Introduction to UNIX
  • Introduction to R I
  • Microbiome
  • Introduction to Reproducible Analysis III
  • Cancer Immunology I
  • Cancer Immunology II
  • Statistics I
  • Statistics II
  • Intro to R II
  • R workshop I
  • Walkthrough experimental paper
  • R workshop II
  • R workshop III
  • R workshop IV: maftools

Week 2 Topics

  • Computational Biology
  • Bioinformatics (dedup, strand bias, coverage, recalibration, contamination)
  • Tutorial: Pre-processing (FASTQ -> recalibrated BAM)
  • Workshop: Pre-processing (FASTQ -> recalibrated BAM)
  • Statistical considerations for germline genotype calling
  • Post-alignment QC (coverage, etc)
  • Tutorial: GATK Haplotype caller (FASTQ -> VCF)
  • Workshop: GATK Haplotype caller (FASTQ -> VCF)
  • DNA-Seq: Statistical considerations for somatic genotype calling
  • GATK Mutect2 Background (tumor purity, PoN, etc)
  • Tutorial: GATK Mutect2 (FASTQ -> VCF)
  • Workshop: GATK Mutect2 (FASTQ -> VCF)
  • Tutorial: IGV/Gviz pileup
  • Workshop: IGV/Gviz pileup
  • Tutorial: Variant annotation (VEP/maftools)
  • Workshop: Variant annotation (VEP/maftools)
  • HLA Calling /MHC Neopeptide prediction
  • Tutorial: HLA Calling
  • Tutorial: MHC Binding Prediction
  • Workshop: HLA Calling and MHC binding prediction

The summer course will be limited to 36 students to optimize the student/faculty ratio and encourage interaction. 12 of these spots are reserved for students who completed the two-week sequence in previous years (2021-2023) the other 24 spots are open for anyone to apply.

Yes. If admitted, you will be required to attend the second week in its entirety. You have the option to attend the first week to review preparatory material. The first week will be largely the same as previous years, but there will be minor modifications. We will make material from the first week available to returning participants, even if they do not attend the first week sessions.

The course is fully funded by the National Cancer Institute (NCI), which covers all costs. As such, there will be no cost to course participants.

The course will be appropriate for participants at many levels of training including advanced undergraduate students, graduate students, postdoctoral fellows, medical doctors, laboratory managers and faculty.

People from backgrounds traditionally underrepresented in STEM are strongly encouraged to apply. Applicants with current or planned research focus on cancer immunology will be given preference for admissions.

Applicants with current or planned research focus on cancer immunology will be given preference for admissions.

Per NIH policy, the course is intended primarily for the education of U.S. citizens and permanent residents.

We will consider highly qualified international applicants who are either enrolled as students or employed by US based institutions or companies.

All students must be located physically within the United States throughout the duration of the course. 

Please apply at the course homepage. Course participants will be accepted on a rolling basis until all spots are filled.

There is no fixed deadline for applications.  We review completed applications on a rolling basis (beginning in early 2024), and offer spots to highly qualified applicants until all spaces are filled.  Once all spaces are filled, we maintain a waitlist in case there are cancellations.

If your application is accepted, cost will will be covered using federal funds provided by the U.S. National Institutes of Health (NIH). If you accept admission to the course, it is expected that you attend all scheduled sessions. Please refer to the posted schedule of classes for the specific days and times covered by this commitment. It is our expectation that you do not schedule conflicting events (e.g., vacations, or work, personal or scientific meetings) during these times. In the application, you will be explicitly asked to affirm your commitment of full attendance.

All students must be located physically within the United States throughout the duration of the course.

In order for your application to be considered, you must:

  • Complete and submit all mandatory portions of the online application form
  • Provide two letters of reference (not required for applicants with faculty-level appointments)

The application management system will automatically generate a link for submission of reference letters.

Course participants will receive neither credit nor a grade for attending the course, and the course will not be recorded in Duke University transcripts. Upon successful completion of the course, a participant will receive a signed certificate issued by the Department of Biostatistics and Bioinformatics. Successful completion requires regular attendance. Absences are only allowed at the discretion of the course instructors.

The course location will be virtual. Students must be physically located within the United States throughout the duration of the course.

The course meets 9AM - 4PM Monday through Friday May 13 – May 24.

The course provides access to computing resources. You will need to use your own laptop or desktop to access these computing resources. You will also need to have access to fast and reliable internet service.

If you have additional questions, please contact the course coordinator.