Genetic Data Interpretation
8 weeks · 0 milestones
Interpret real genetic data from a named publicly available source: annotate a set of variants using ClinVar and Ensembl Variant Effect Predictor (VEP — free), interpret a GWAS result from a published study by tracing a named variant through the statistical and functional evidence, or analyse sequencing results for a named genetic question using published population data. Document the evidence base for each interpretation claim: variant frequency, functional consequence predictions, clinical significance classifications, and limitations of the evidence. Reviewed by a geneticist or bioinformatician who presents an unseen variant of uncertain significance during the review session and asks you to classify it and justify the classification using ACMG/AMP variant interpretation criteria — requiring real-time reasoning about evidence quality, not recall of known variant classifications. All data sources and annotation tools are freely accessible.
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3 milestones
Define the specific genetic question you will investigate and identify an appropriate freely available dataset to address it. Accessible alternative: all routes for this outcome use open genomic databases — no physical laboratory access is required. NCBI SRA contains millions of publicly deposited sequencing datasets; Ensembl provides genome annotation and comparative genomics data; NCBI dbSNP and published GWAS summary statistics are freely downloadable.
Proof required
Submit your genetic research question (specific enough to produce an answerable result), the dataset you have selected with its accession number and source URL, a description of the biological context (organism, tissue, condition, or population), and a brief justification of why this dataset is appropriate for your question.
What gets checked
- Genetic question is specific and answerable — not 'understand how genes work' but 'compare the variant frequency of rs334 between African and European populations in the 1000 Genomes data'
- Dataset source is authoritative (NCBI SRA, Ensembl, 1000 Genomes, GTEx, GWAS Catalog, or equivalent) with an accessible accession number
- Biological context is described at sufficient depth to interpret the results — organism, tissue or population, and what biological question the analysis addresses