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Record W2788447140 · doi:10.1503/cmaj.171151

The Personal Genome Project Canada: findings from whole genome sequences of the inaugural 56 participants

2018· article· en· W2788447140 on OpenAlexvenueaboutno aff
Miriam S. Reuter, Susan Walker, Bhooma Thiruvahindrapuram, J. Andrew Whitney, Iris Cohn, Neal Sondheimer, Ryan K. C. Yuen, Brett Trost, Tara Paton, Sérgio L. Pereira, Jo-Anne Herbrick, Richard F. Wintle, Daniele Merico, Jennifer Howe, Jeffrey R. MacDonald, Chao Lu, Thomas Nalpathamkalam, Wilson W. L. Sung, Zhuozhi Wang, Rohan Patel, Giovanna Pellecchia, John Wei, Lisa J. Strug, Sherilyn L. Bell, Barbara Kellam, Melanie M. Mahtani, Anne S. Bassett, Yvonne Bombard, Rosanna Weksberg, Cheryl Shuman, Ronald D. Cohn, Dimitri J. Stavropoulos, Sarah Bowdin, Matthew R. Hildebrandt, Wei Wei, Asli Romm, Peter Pasceri, James Ellis, Peter N. Ray, M. Stephen Meyn, Nasim Monfared, S. Mohsen Hosseini, Ann M. Joseph‐George, Fred W. Keeley, R Cook, Marc Fiume, Hin C Lee, Christian R. Marshall, Allison Hazell, Janet A. Buchanan, Michael J. Szego, Stephen W. Scherer

Bibliographic record

VenueCanadian Medical Association Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsPersonal genomicsGeneticsGenomeWhole genome sequencingBiologyDNA sequencing1000 Genomes ProjectGenotypeGeneSingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

BACKGROUND: The Personal Genome Project Canada is a comprehensive public data resource that integrates whole genome sequencing data and health information. We describe genomic variation identified in the initial recruitment cohort of 56 volunteers. METHODS: Volunteers were screened for eligibility and provided informed consent for open data sharing. Using blood DNA, we performed whole genome sequencing and identified all possible classes of DNA variants. A genetic counsellor explained the implication of the results to each participant. RESULTS: Whole genome sequencing of the first 56 participants identified 207 662 805 sequence variants and 27 494 copy number variations. We analyzed a prioritized disease-associated data set (n = 1606 variants) according to standardized guidelines, and interpreted 19 variants in 14 participants (25%) as having obvious health implications. Six of these variants (e.g., in BRCA1 or mosaic loss of an X chromosome) were pathogenic or likely pathogenic. Seven were risk factors for cancer, cardiovascular or neurobehavioural conditions. Four other variants — associated with cancer, cardiac or neurodegenerative phenotypes — remained of uncertain significance because of discrepancies among databases. We also identified a large structural chromosome aberration and a likely pathogenic mitochondrial variant. There were 172 recessive disease alleles (e.g., 5 individuals carried mutations for cystic fibrosis). Pharmacogenomics analyses revealed another 3.9 potentially relevant genotypes per individual. INTERPRETATION: Our analyses identified a spectrum of genetic variants with potential health impact in 25% of participants. When also considering recessive alleles and variants with potential pharmacologic relevance, all 56 participants had medically relevant findings. Although access is mostly limited to research, whole genome sequencing can provide specific and novel information with the potential of major impact for health care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.226
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations64
Published2018
Admission routes2
Has abstractyes

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