Late-breaking abstract: Genapha/dbASM: Investigating allele-specific methylation (ASM) and associations to common complex diseases
Bibliographic record
Abstract
As interest in studying allele-specific methylation (ASM) grows, there is a need for a resource that stores and catalogs SNPs and regions that demonstrate allele specific methylation, analogous to dbSNP. We have created a new web resource called dbASM, hosted on the Genapha web server (www.genapha.ca),in order to help fulfill this need. The aim of dbASM is twofold: 1. Curate from the literature a publicly-accessible database of known sites of ASM. 2. Provide a web-based platform of tools for exploring ASM and determining regions of interest. These regions of interest can then be assayed for methylation status using small, custom arrays that are currently cheaper than using whole-genome approaches such as the Illumina 450K or bisulphite sequencing. We present the dbASM resource including details on the underlying database construction and datasets, in addition to the web tools and example workflows. The web tools that are currently available are: GWAS Catalog SNP Search, ASM SNP Search, SNP Counter, Methylation Plots Generation, and Sequence Viewer. GWAS Catalog SNP Search allows browsing through NHGRI's Catalog of Published Genome-Wide Association Studies by phenotype and filtering SNPs based on their relation to suspected sites of ASM. ASM SNP Search supports finding SNPs based on: ASM status or interrogability; location compared to genes, a chromosomal region, or other SNP's; and filtering by population minor allele frequencies and sample size. Methylation Plots Generation calculates SNP correlation stratifying by genotype with CpG site methlyation patterns from the HapMap population. These tools are all freely available for use at: http://genapha.icapture.ubc.ca/asm/.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.094 | 0.044 |
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 source (direct Gemma or distilled Codex), 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".