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ArticlemedRxiv : the preprint server for health sciences2026

'Truthsets' for clinical validation of large-scale functional assays: Practice recommendations from Cancer Variant Interpretation Group UK (CanVIG-UK).

Sophie Allen, Charlie F Rowlands, Alice Garrett, Zeid Kuzbari, Miranda Durkie, George J Burghel, Rachel Robinson, Alison Callaway, Joanne Field, Bethan Frugtniet and 22 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

32 authors.

Sophie AllenDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.ORCID 0000-0003-4928-2240
Charlie F RowlandsDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.ORCID 0000-0001-5333-4846
Alice GarrettDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.ORCID 0000-0001-8942-283X
Zeid KuzbariDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.ORCID 0000-0001-7856-1578
Miranda DurkieNorth East and Yorkshire Genomic Laboratory Hub, Sheffield Children's NHS Foundation Trust, Sheffield, UK.ORCID 0000-0001-7071-7048
George J BurghelDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID 0000-0001-9360-8194
Rachel RobinsonThe Leeds Genetics Laboratory, NEY Genomic Laboratory Hub, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Alison CallawayCentral and South Genomics Laboratory Hub, Wessex Genomics Laboratory Service, University Hospital Southampton NHS Foundation Trust, Salisbury, UK.ORCID 0000-0002-9236-7891
Joanne FieldNottingham Genomics Laboratory Service, Nottingham University Hospitals NHS Trust, Nottingham, UK.
Bethan FrugtnietSt George's University Hospitals NHS Foundation Trust, Tooting, London, UK.
Sheila Palmer-SmithWales Genomic Health Centre, Cardiff and Vale University Health Board, Cardiff, UK.
Jonathan GrantWest of Scotland Centre for Genomic Medicine, Queen Elizabeth University Hospital, Glasgow, UK.
Judith PaganSouth East Scotland Clinical Genetics, Western General Hospital, Edinburgh, UK.
Elizabeth JohnstonNottingham Genomics Laboratory Service, Nottingham University Hospitals NHS Trust, Nottingham, UK.
Trudi McDevittDepartment of Clinical Genetics, CHI at Crumlin, Dublin, Ireland.ORCID 0009-0008-2425-5194
Lowri HughesWest Midlands Genomics Laboratory, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.
Laura Yarram-SmithNorth Bristol NHS Trust, Southmead Hospital, Bristol, UK.
Peter LoganBelfast Health and Social Care Trust, Royal Victoria Hospital, Belfast, UK.
Laura ReedRare & Inherited Disease Laboratory, NHS North Thames Genomic Laboratory Hub, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
Katie SnapeSt George's University Hospitals NHS Foundation Trust, Tooting, London, UK.ORCID 0000-0002-1739-7986
Terri McVeighThe Royal Marsden NHS Foundation Trust, Fulham Road, London.ORCID 0000-0001-9201-9216
Helen HansonPeninsula Regional Genetics Service, Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK.ORCID 0000-0002-3303-8713
Rehan VillaniPopulation Health Program, QIMR Berghofer, Brisbane, QLD, Australia.ORCID 0000-0001-8857-6271
Amanda B SpurdlePopulation Health Program, QIMR Berghofer, Brisbane, QLD, Australia.ORCID 0000-0003-1337-7897
Lea M StaritaDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2870-5099
Douglas M FowlerDepartment of Bioengineering, University of Washington, Seattle, WA 98195.ORCID 0000-0001-7614-1713
Frederick P RothDepartment of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.ORCID 0000-0002-6628-649X
Elizabeth RadfordWellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.ORCID 0000-0002-7829-5422
David J AdamsWellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.ORCID 0000-0001-9490-0306
Gregory M FindlayThe Genome Function Laboratory, The Francis Crick Institute, London, UK.ORCID 0000-0002-7767-8608
Clare TurnbullDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.ORCID 0000-0002-1734-5772
CanVIG-UK

Funding

The Center for Actionable Variant Analysis; measuring variant function at scaleUM1HG011969 · NHGRI · UNIVERSITY OF WASHINGTON · PI Douglas M Fowler, Lea Starita · 2021 to 2026
$9.9M
NHGRI NIH HHS UM1 HG011969
6 · The paper itself

Abstract

Background: Large-scale functional assays, including multiplex assays of variant effect, have substantial potential to resolve variants of uncertain significance (VUS), particularly for rare missense variants where clinical and population evidence are limited. The ClinGen assay-level clinical validation framework described by Brnich et al provided baseline guidance for the use of functional data for variant classification. However, clear consensus regarding construction of variant 'truthsets' by which to clinically validate functional data remains lacking. Methods: CanVIG-UK developed consensus recommendations for truthset construction through an iterative national consultation process involving the CanVIG Steering Advisory Group (CStAG), wider CanVIG-UK membership, and engagement with international functional genomics experts. Consultation was based on previous analyses of 2,120 truthset constructions examining the impact of truthset composition on evidence point allocation within the ClinGen assay-level clinical validation framework. Results: Across several consultations, CanVIG-UK established nine guiding principles and seven best-practice recommendations for assay-level clinical validation, using the assumed context of an assay for a cancer susceptibility gene where loss-of-function is the mechanism of pathogenicity. The principal recommendation stipulates, where assays are intended for use in interpretation of largely missense variants, the truthset used to validate should comprise only missense variants. Rather than mixtures of different variant types which may serve to over-estimate assay performance. Additional recommendations support option for relaxation of truthset stringency to improve power, augmentation of benign missense truthsets with systematically derived 'proxy-clinical' benign variants, independent clinical validation separate from assayist-defined validation, and careful evaluation of missense score distributions against that of protein-truncating and synonymous variants. Guidance is also provided for scenarios with limited pathogenic truthset availability and for assays reporting multiple deleterious zones or readouts. Conclusions: The CanVIG-UK principles and recommendations for truthset construction upon the ClinGen assay-level clinical validation framework, while aiming to form a baseline for future discussion regarding other functional and disease contexts and helping to address the gap between publication of new data and routine clinical implementation.

Identifiers

PMID42528494
PMCPMC13409263

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