ENAR 2026 DataFest
We are seeking ENAR Student members, who are degree candidates at an accredited institution in any term during 2025-26 academic year to participate in the ENAR 2026 DataFest event. Student teams will work with one of the datasets provided for this competition to answer an important scientific question.
Up to four teams will be invited to present at the ENAR 2026 Spring Meeting. Each final four team will receive individual team member certificates, discounted Spring Meeting registration, and an invitation for a 20-minute presentation as part of the ENAR DataFest Invited Session. The team with the most outstanding final presentation will receive the ENAR DataFest Award, which includes an additional monetary prize.
We are also seeking volunteers to serve as mentors and judges. See below for more information! We encourage you to share the flyer here with your students, colleagues and friends.
Eligibility
To be eligible, a student team must include 2-4 individuals, who are all current ENAR members, degree candidates (master’s or doctoral level students) at an accredited institution in any term during 2025-26 academic year, and able to present their project at the ENAR Spring Meeting, March 15-18, 2026, in Indianapolis, Indiana.
Key Deadlines
Nov. 19: WebENAR | DataFest 2026 Information Session for Students and Mentors (Check out the slides here and the recording here!)
Dec. 5: DataFest Team, Mentors and Judge Interest Forms Due!
Dec. 15: Student teams paired with a mentor.
Dec. 15 - Jan. 26: Project working window.
Jan. 26: DataFest Project Submission Form Due.
Feb. 9: Final 4 winners announced.
Mar 16: Final 4 teams present at ENAR 2026 Spring Meeting.
DataFest Project Summary
Teams will choose one of the datasets provided for this competition to answer an important scientific question. The statistical analysis should consider a problem, issue or policy question relevant to the problem statement. A brief description of each dataset is provided below:
Requirements:
- Formulate a clear and testable hypothesis.
- Apply appropriate statistical, computational, or machine learning methods.
- Present results with visualizations, interpretation, and actionable insights.
- Discuss limitations, data quality issues, and implications for public health or clinical practice.
Expected Outcome:
Projects should demonstrate creativity in data use, rigor in analysis, and clarity in communication - translating complex data into insights that advance understanding of population health.
1. NHANES Dataset
Problem statement: Participants are invited to explore the National Health and Nutrition Examination Survey (NHANES)--a large-scale and publicly available datasets--to address an important question in population health, chronic disease prevention, health disparities and related areas. Teams should develop their own hypothesis, perform rigorous data cleaning and analysis, and generate evidence-based insights using appropriate statistical or computational methods.
Data Description (from the NHANES website): The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The survey is unique in that it combines interviews and physical examinations. NHANES is a major program of the National Center for Health Statistics (NCHS). NCHS is part of the Centers for Disease Control and Prevention (CDC) and has the responsibility for producing vital and health statistics for the Nation.
The NHANES program began in the early 1960s and has been conducted as a series of surveys focusing on different population groups or health topics. In 1999, the survey became a continuous program that has a changing focus on a variety of health and nutrition measurements to meet emerging needs. The survey examines a nationally representative sample of about 5,000 persons each year. These persons are located in counties across the country, 15 of which are visited each year.
The NHANES interview includes demographic, socioeconomic, dietary, and health-related questions. The examination component consists of medical, dental, and physiological measurements, as well as laboratory tests administered by highly trained medical personnel.
NHANES data are widely used in public health and biomedical research, contributing to thousands of peer-reviewed studies that inform national health policy and clinical guidelines.
Data Resources: NHANES provides detailed information on demographics, clinical measurements, laboratory tests, lifestyle factors, and comorbidities across U.S. adults and children. Documentation and raw datasets can be accessed through the following link https://wwwn.cdc.gov/nchs/nhanes/Default.aspx. Please also refer to supporting materials here.
2. TCGA Dataset
cBioPortal Website Description:
cBioPortal is an open-access, open-source platform designed to facilitate intuitive, interactive exploration, visualization, and analysis of multidimensional cancer genomics and clinical datasets. Originally developed by Memorial Sloan Kettering Cancer Center and now maintained by a multi-institutional collaboration, it hosts a broad array of large-scale studies (including TCGA, Pan-Cancer Atlas, and AACR Project GENIE), offering data on mutations, copy number alterations, gene expression, methylation, proteomics, and clinical annotations.
Problem statement:
Patient survival prediction has always been a critical question in cancer research, contributing to both risk stratification and treatment decision-making. Although TCGA data has been publicly available for years, how to effectively integrate data across multiple omics modalities to enhance survival prediction remains an open challenge. We invite teams interested in omics research to analyze publicly available data from the cBioPortal platform. For this project, we provide downloaded data from the TCGA breast cancer study. However, the cBioPortal hosts many additional datasets across various cancer types. These comprehensive resources enable researchers to either focus deeply on a specific cancer type or to conduct integrative analyses across multiple cancers. While survival prediction is one avenue of investigation, other important questions in cancer biology and treatment can also be explored. We encourage teams to think creatively about how TCGA data can be used to advance modeling and predictive efforts in cancer research.
Data Description:
- Data from a TCGA breast cancer study were downloaded from the cBioPortal website (https://www.cbioportal.org/study/summary?id=breast_msk_2025). The dataset includes multiple datasheets that can be linked by patient ID and sample ID (note that one patient may have multiple samples).
- The datasheets include:
- Data_clinical_patient.txt: Contains clinical information about patients, including diagnosis, treatments received, age at diagnosis, overall survival time, and survival status.
- Data_clinical_sample.txt: Provides details about the tumor samples, such as the associated patient, tumor site, stage, and other sample-specific annotations.
- Data_methylation_promoters_rrbs.txt: Contains gene-level methylation data across samples.
- Data_mrna_illumina_microarray.txt: Includes normalized mRNA expression levels from Illumina microarrays.
- Data_mutation.txt: Contains mutation data for the tumor samples.
Accessing Additional TCGA Data for other cancer types: We encourage teams to explore and integrate additional datasets or analyze data from multiple cancer types available through the cBioPortal website (https://www.cbioportal.org/datasets).
Guidelines for DataFest Preparation
All required materials for ENAR DataFest must be received by the ENAR Business Office, including the electronic submission of the manuscript and video presentation through www.enar.org, by 11:59 p.m. ET January 26th, 2026. Only complete submissions that meet the eligibility requirements, follow the described guidelines, and are received by January 26th will be considered. Teams will submit a GitHub repository that includes:
- A maximum 5-page report with up to 2 figures and 2 tables
- A 5-minute video presentation
- Associated reproducible code base.
Guidelines Checklist
Please use the following Guidelines Checklist to confirm your submission is complete before submitting for participation in the ENAR DataFest. If you do not meet these criteria, your project may be disqualified. Out of respect for all teams, NO EXCEPTIONS to the eligibility criteria or submission deadlines will be made. Please read these details carefully and plan ahead! If you have questions about DataFest, please email enar@enar.org and include DataFest in the subject line.
To be considered complete:
Your submission should include:
- a manuscript submitted as pdf
- a maximum 5-minute video submitted as MP4
- a brief abstract (1200-character count max)
- a GitHub repository with a reproducible code
- Link or text describing your additional data source
A manuscript should include:
- a maximum of 25 lines per page, double spaced
- 1-inch margins
- 12-point font
- a maximum of 5 pages*
- a title page with a title, a brief abstract (1 paragraph in length) and keywords
- References typed using the style of the Biometrics journal
- Tables and figures at the end of manuscript
- no more than FOUR (4) tables and/or figures
*Title page, up to 2 tables and 2 figures and references are NOT included in the 5-page limit.
A manuscript should NOT include:
- supplemental materials
A video submission should be no longer than 5 minutes and include:
- a problem statement
- a statistical analysis overview
- key results
- conclusion
Review Criteria
- Clarity of research purpose and motivation by a relevant problem.
- Innovative approach that is relevant to the motivating question.
- Scientifically meaningful results are clearly explained and/or illustrated.
- Organization of the article and presentation is clear and concise.
- Avoid using ChatGPT or other generative AI tools to produce manuscripts, abstracts, code, or analyses that are presented as their own original work.
- When generative AI tools are used for minor tasks such as grammar checking or brainstorming, this must be transparently disclosed in the methods or acknowledgment section, as appropriate.
Submission of DataFest Projects
Submission of DataFest Projects
You are required to complete Steps 1 & 2 by each respective deadline.
STEP 1: Electronic Submission of Student Interest Form.
The Student Interest Form must be submitted no later than 11:59 p.m. EST Friday, December 5, 2025.
STEP 2: Electronic Submission of DataFest Project Submission Form.*
All projects and supporting documentation must be submitted no later than 11:59 p.m. EST Monday, January 26th, 2026.
*Required: GitHub Repository (with reproducible code and report) AND Video Presentation
ENAR DataFest Submission Forms
Judge or Mentor Interest Form
We seek ENAR members who are either faculty or working professionals to serve as either DataFest judges or mentors.
- Judges will be tasked with scoring submitted project reports, consisting of a 5-minute video presentation and review of a reproducible codebase. Rubrics will be provided to guide the judging process. Judge interest forms are due by Friday, December 5, 2025.
- Mentors will be paired with an assigned team(s). Mentors will review the grading rubrics to gain a deeper understanding of the topics that each team will be assessed on. Mentors can serve as judges only for teams they do not mentor. Mentor interest forms are due by Friday, December 5, 2025.
Student Team Interest Form
We are seeking PhD and Masters students, who are interested in participating in the second annual ENAR DataFest. Student teams can be made up of 2-4 members. One member from your team should complete the DataFest Submission Form and include all member names, emails and affiliations. Student interest forms are due by Friday, December 5, 2025.
DataFest Project Submission Form
Please submit your projects using the form below. We request information on all student team members (max 4), a link to the reproducible code-base shared via GitHub, and a video submission or link to video submission consisting of the 5-minute DataFest project presentation. DataFest Project Submission forms are due by Monday, January 26, 2026.