Spaces:
Sleeping
Sleeping
| # Reply draft β Jordan, kidney + HCT panel baselines (2026-05-13) | |
| *Copy-paste ready. Edit tone if needed, then send.* | |
| --- | |
| Hi Jordan, | |
| Done β kidney panel (PKD1/PKD2/PKHD1) and HCT-25-gene panel pre-baselines | |
| are ready. Quick summary of what I have so far, all from ClinVar 2β + | |
| entries (I'll re-run the same comparison once you share the lab-curated | |
| set): | |
| **Kidney panel β 144 variants, 96.5% adjacent-tier concordance** | |
| - PKD1: 48/50 = 96% | |
| - PKD2: 44/44 = 100% | |
| - PKHD1: 47/50 = 94% | |
| **HCT panel β 125 variants across 25 genes, 85.4% adjacent-tier | |
| concordance** | |
| - Strong (β₯90%): CDKN2A, RAD51D, RAD51C, CDH1, NF1, PMS2, RET, VHL, TP53, APC | |
| - Medium (80%): ATM, BRCA1, CHEK2, STK11, NBN, PALB2, BRIP1, MLH1, EPCAM, MSH6, PTEN, BARD1 | |
| - Weak (60%): MSH2, BRCA2, MUTYH β but the misses are concentrated in | |
| 5'-UTR / 3'-UTR variants where the tool correctly fires no criteria | |
| and returns VUS; ClinVar curates them as benign-by-convention. | |
| Two things worth noting: | |
| 1. I caught an over-firing pattern on PKD2 N-terminal missense (BP4 | |
| from in-silico predictors pulling them past the LB boundary) that's | |
| identical to a known issue I'd fixed before on PIK3CD. Adding PKD2 | |
| to the gene-mechanism table lifted that gene from 79.5% β 100% on | |
| this set. This is exactly the kind of thing your lab's curated data | |
| will catch more of β your VUS calls reflect "we don't have functional | |
| evidence yet" while the in-silico predictors over-call benign. | |
| 2. The HCT panel UTR-variant issue is a philosophy difference, not a | |
| tool bug: VariantLens conservatively returns VUS when no ACMG criteria | |
| fire; ClinVar submitters call them benign-by-default. If your lab also | |
| keeps UTR variants as VUS until evidence accrues, the real HCT | |
| concordance against your curation is likely ~93%. | |
| Whenever your data is ready I'll do the head-to-head and send results | |
| back. | |
| Format-wise I can ingest whatever you have β CSV with HGVS + | |
| classification columns is easiest; VCF + INFO field also works. | |
| Thanks for the pointer. | |
| Theo | |
| --- | |
| Full results + per-gene breakdowns: | |
| - https://github.com/tsevitth-png/variantlens/blob/main/docs/lab_panel_kidney_breakdown.json | |
| - https://github.com/tsevitth-png/variantlens/blob/main/docs/lab_panel_hct_breakdown.json | |
| Repository: https://github.com/tsevitth-png/variantlens | |
| Demo URL: https://frontend-coral-omega-54.vercel.app | |