Mapping trans-methylation quantitative trait loci in the human genome
Melody Heeju Hong · Wantagh, New York
Sixth Place ($80,000) · Regeneron Science Talent Search · 2025
A statistical model for locating trans-methylation quantitative trait loci — genetic variants that influence DNA methylation at distant sites rather than nearby ones.
Trans effects are weaker and far harder to detect than local ones, which is exactly why they are under-mapped. Choosing the harder signal is a defensible reason for a methods project to exist.
- Statistical model development
- Trans-QTL mapping
- DNA methylation data analysis
- Multiple-testing correction
- Targeting the effect everyone else filters out is a legitimate niche
- Statistical genetics lives on multiple-testing correction; say how you handled it before you are asked
Archive entries are summaries compiled for study. Read them for how a project was structured, argued, and defended — not as a template to reproduce. Copying someone else's project is the one thing that will end yours.
Compiled by ResearchForge from the Society for Science public award announcement linked on this record. Names, hometowns, project titles and reported results are as published. The "why it worked" and "what to take from this" notes are ResearchForge's editorial reading of that public record — they are not statements by the students and not the judges' rationale. All rights to the original projects remain with their authors; no project materials are rehosted here.