Evidence map›Paper›PMID 42729822›Full record

ArticleBioinformatics advances2026

PanelAppRex aggregates disease gene panels and facilitates sophisticated search.

Quant Group, Simon Boutry, Ali Saadat, Sinisa Savic, Luregn J Schlapbach, Jacques Fellay, Dylan Lawless

Abstract read
In one paragraph

Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Application of qualifying variants for genomic analysis.Bioinformatics (Oxford, England) · 2026
    Article
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

7 authors.

Quant GroupThe Quantitative Omics Epidemiology Group.
Simon BoutryGlobal Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
Ali SaadatGlobal Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
Sinisa SavicLeeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Luregn J SchlapbachDepartment of Intensive Care and Neonatology, University Children's Hospital Zurich, University of Zurich, Zurich 8008, Switzerland.
Jacques FellayGlobal Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.ORCID https://orcid.org/0000-0002-8240-939X
Dylan LawlessDepartment of Intensive Care and Neonatology, University Children's Hospital Zurich, University of Zurich, Zurich 8008, Switzerland.ORCID https://orcid.org/0000-0001-8496-3725

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Gene panel data are essential for variant interpretation and genomic diagnostics, but existing resources are fragmented, inconsistently annotated, and not easily accessible for programmatic use. We developed PanelAppRex, a harmonised dataset and interactive search tool that integrates over 58 000 curated gene-disease panel associations. It supports natural language-style queries by gene, phenotype, disease group, and mode of inheritance, with results returned in machine-readable export formats. Results: The resulting dataset includes standardised gene identifiers, disease annotations, mode of inheritance, and literature support, enabling seamless integration into bioinformatic pipelines. We benchmarked 15 case studies spanning immunology, neurology, and additional disease areas. Under the recommended usage, in which the union of returned panels is considered, the causal gene was recovered in every case. Across all returned panels, the causal gene was present in 85.6% of panels. For manual interface interpretation, the causal gene was present in the user-selected best-fit panel(s) in all 15 benchmarked cases. Availability: The platform data is openly available at Zenodo https://doi.org/10.5281/zenodo.15736689, with source code at https://github.com/DylanLawless/PanelAppRex, and demonstration page at https://panelapprex.github.io/landing_page. The dataset is maintained for a minimum of two years following publication.

Identifiers

PMID42729822
PMCPMC13563085

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.