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33:T498,Inputs.table(filteredOverlap, { columns: [ "pgsId", "name", "trait", "variantsInFile", "v2_overlapPercent", "v3_overlapPercent", "v4_overlapPercent", "v5_overlapPercent", "v5_matched", "v5_missing" ], header: { pgsId: "PGS ID", name: "Model", trait: "Trait", variantsInFile: "SNPs", v2_overlapPercent: "v2 %", v3_overlapPercent: "v3 %", v4_overlapPercent: "v4 %", v5_overlapPercent: "v5 %", v5_matched: "Matched", v5_missing: "Missing" }, width: { pgsId: 95, name: 115, trait: 110, variantsInFile: 60, v2_overlapPercent: 65, v3_overlapPercent: 65, v4_overlapPercent: 65, v5_overlapPercent: 65, v5_matched: 75, v5_missing: 75 }, format: { trait: d => d?.length > 20 ? d.slice(0, 20) + "…" : d, v2_overlapPercent: d => d == null ? "" : `${Number(d).toFixed(1)}%`, v3_overlapPercent: d => d == null ? "" : `${Number(d).toFixed(1)}%`, v4_overlapPercent: d => d == null ? "" : `${Number(d).toFixed(1)}%`, v5_overlapPercent: d => d == null ? "" : `${Number(d).toFixed(1)}%` }, rows: 10, maxWidth: 950, select: false })34:Tc71,## Inputs | Source | Location | |---|---| | PGS scoring files | `gs://allpgs/scores/GRCh37/` | | v2 manifest | `gs://all23_0710/chip_manifests/v2_build37_95pct/` | | v3 manifest | `gs://all23_0710/chip_manifests/v3_build37_95pct/` | | v4 manifest | `gs://all23_0710/chip_manifests/v4_build37_95pct/` | | v5 manifest | `gs://all23_0710/chip_manifests/v5_build37_95pct/` | Each chip directory contains `manifest.json` and `variant_manifest_core.json`. **Core definition:** SNP coordinates present in ≥95% of the sampled files for each chip. ## Processing 1. Load v2–v5 GRCh37 core manifests. 2. Identify PGS models with ≤1,000 scoring-file rows. 3. Parse harmonized PGS scoring files. 4. Match SNPs by `chromosome:position`. 5. Deduplicate coordinates and validate variant records. 6. Calculate direct overlap for each chip (0–100%). 7. Generate model-level reports, summary statistics, and QC results. **Matching:** GRCh37 coordinates are primary; rsIDs are retained for diagnostics. ## Results ### Chip manifest coverage | Chip | 23andMe files | Core SNP positions | |---|---:|---:| | v2 | 3 | 544,839 | | v3 | 17 | 959,702 | | v4 | 74 | 596,247 | | v5 | 64 | 622,753 | ### PGS model overlap All four chips were compared against 1,759 PGS models. | Metric | v2 | v3 | v4 | v5 | |---|---:|---:|---:|---:| | Mean overlap | 28.21% | **41.29%** | 32.13% | 31.48% | | Models ≥80% | 31 | 71 | 39 | **121** | | Models ≥95% | 10 | 27 | 15 | **32** | | Models 100% | 10 | **24** | 13 | 22 | ### Key findings - **v3** has the highest average direct SNP coverage. - **v5** has the most models passing the ≥80% overlap filter (121/1,759; 6.9%). - **v4** has 39/1,759 models passing the same filter (2.2%). - Some PGS IDs share identical or highly overlapping SNP sets, so model counts do not necessarily represent unique variant panels. - Models with low direct coverage are candidates for imputation. - Direct overlap is not equivalent to genotype accuracy or predictive performance. ## Outputs ```text gs://all23_0710/pgs_overlap_v2_v5_95pct/ ├── README.md ├── summary.json ├── results/ │ ├── overlap_v2_0_100.json │ ├── overlap_v3_0_100.json │ ├── overlap_v4_0_100.json │ ├── overlap_v5_0_100.json │ └── model_chip_overlap.csv └── qc/ ├── validation_summary.json └── failed_pgs.json ``` ## Diseasome Tab 2 Integration Use precomputed overlap results to support: - Filter by chip version (v2, v3, v4, v5). - Filter by PGS model size (≤1,000 variants). - Filter by SNP overlap threshold (≥80%, ≥90%, ≥95%, 100%). - Display matched/missing variant counts and QC information. - Join PGS Catalog metadata for model names, traits, publications, and licenses. - Identify models requiring FastImpute or other imputation methods. **Next:** Combine the overlap reports with PGS Catalog metadata into a browser-ready model-selection dataset. **Note:** The 95% chip-core presence threshold is separate from the 0–100% PGS model-overlap percentage. These results replace the earlier 20-file v4/v5 analysis and should not be interpreted as imputation or PRS 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d.trait).filter(Boolean))\n ].map(String).sort((a, b) =>\n a === \"All traits\" ? -1 :\n b === \"All traits\" ? 1 :\n a.localeCompare(b)\n ),\n {\n label: \"Filter by trait\",\n value: \"All traits\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":45,"value":"viewof modelSearch = Inputs.text({\n label: \"Search PGS models\",\n placeholder: \"Type PGS ID, model name, or trait...\",\n submit: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":46,"value":"filteredOverlap = model_23chip_overlap.filter(d => {\n const traitMatch =\n selectedTrait === \"All traits\" ||\n d.trait === selectedTrait;\n\n const q = modelSearch.trim().toLowerCase();\n\n const searchMatch = [\n d.pgsId,\n d.name,\n d.trait\n ].some(v => String(v ?? \"\").toLowerCase().includes(q));\n\n return traitMatch && searchMatch;\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"v5 = FileAttachment(\"overlap_v5_0_100.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"v4 = 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