Genome‐wide linkage analysis of 1,233 prostate cancer pedigrees from the International Consortium for prostate cancer Genetics using novel sumLINK and sumLOD analyses
Bibliographic record
Abstract
BACKGROUND: Prostate cancer (PC) is generally believed to have a strong inherited component, but the search for susceptibility genes has been hindered by the effects of genetic heterogeneity. The recently developed sumLINK and sumLOD statistics are powerful tools for linkage analysis in the presence of heterogeneity. METHODS: We performed a secondary analysis of 1,233 PC pedigrees from the International Consortium for Prostate Cancer Genetics (ICPCG) using two novel statistics, the sumLINK and sumLOD. For both statistics, dominant and recessive genetic models were considered. False discovery rate (FDR) analysis was conducted to assess the effects of multiple testing. RESULTS: Our analysis identified significant linkage evidence at chromosome 22q12, confirming previous findings by the initial conventional analyses of the same ICPCG data. Twelve other regions were identified with genome-wide suggestive evidence for linkage. Seven regions (1q23, 5q11, 5q35, 6p21, 8q12, 11q13, 20p11-q11) are near loci previously identified in the initial ICPCG pooled data analysis or the subset of aggressive PC pedigrees. Three other regions (1p12, 8p23, 19q13) confirm loci reported by others, and two (2p24, 6q27) are novel susceptibility loci. FDR testing indicates that over 70% of these results are likely true positive findings. Statistical recombinant mapping narrowed regions to an average of 9 cM. CONCLUSIONS: Our results represent genomic regions with the greatest consistency of positive linkage evidence across a very large collection of high-risk PC pedigrees using new statistical tests that deal powerfully with heterogeneity. These regions are excellent candidates for further study to identify PC predisposition genes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".