Evidence map›Paper›PMID 41470026›Full record

ArticleGenome medicine2025

An integrated platform for concurrent structural and single-nucleotide variants improves copy-number detection and reveals pathogenic alleles in undiagnosed Mendelian families.

Haowei Du, Ming Yin Lun, Lidiia Gagarina, Jesse D Bengtsson, Christopher M Grochowski, Michele G Mehaffey, James Paul Hwang, Shalini N Jhangiani, Sravya V Bhamidipati, Donna M Muzny and 9 more

Abstract read
In one paragraph

Article in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

19 authors.

Haowei Du *Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
Ming Yin Lun *Pacific Northwest Research Institute, Seattle, WA, 98122, USA.
Lidiia GagarinaPacific Northwest Research Institute, Seattle, WA, 98122, USA.
Jesse D BengtssonPacific Northwest Research Institute, Seattle, WA, 98122, USA.
Christopher M GrochowskiHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Michele G MehaffeyPacific Northwest Research Institute, Seattle, WA, 98122, USA.
James Paul HwangHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Shalini N JhangianiHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Sravya V BhamidipatiHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Donna M MuznyHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
M Cecilia PoliProgram of Immunogenetics and Translational Immunology, Faculty of Medicine, Clínica Alemana-Universidad del Desarrollo, 7610658, Santiago, Chile.
Sebastian OchoaDepartment of Pediatrics, Section of Immunology, Allergy, and Retrovirology, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, 77030, USA.
Ivan K ChinnDepartment of Pediatrics, Section of Immunology, Allergy, and Retrovirology, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, 77030, USA.
Anna LindstrandDepartment of Molecular Medicine and Surgery, Karolinska Institutet, 17176, Stockholm, Sweden.
Jennifer E PoseyDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
Richard A GibbsDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
Pengfei LiuDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
James R LupskiDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA. jlupski@bcm.edu.
Claudia M B CarvalhoPacific Northwest Research Institute, Seattle, WA, 98122, USA. ccarvalho@pnri.org.

Funding

Baylor-Johns Hopkins Center for Mendelian GeneticsUM1HG006542 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI VALLE, DAVID · 2016 to 2020
$14.5M
Frequency of variants of unknown significance by ancestry groups in the All of Us Research Program cohortU01HG011758 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI RICHARD A GIBBS, JAMES R. LUPSKI · 2021 to 2026
$13.8M
Preclinical and Clincial OutcomesP50HD103555 · NICHD · BAYLOR COLLEGE OF MEDICINE · PI Sandesh Chakravarthy Sreenath Nagamani, David Loren Nelson · 2020 to 2026
$9.9M
STRUCTURAL VARIATION IN NEUROLOGICAL DISEASER35NS105078 · NINDS · BAYLOR COLLEGE OF MEDICINE · PI LUPSKI, JAMES R. · 2018 to 2025
$6.0M
Uncovering inversion formation in the human genome and its impact to disease.R01GM132589 · NIGMS · PACIFIC NORTHWEST RESEARCH INSTITUTE · PI FONSECA, CLAUDIA CARVALHO · 2020 to 2024
$3.5M
NHGRI NIH HHS U01 HG011758NHGRI NIH HHS UM1 HG006542NHLBI NIH HHS UM1 HG006542NICHD NIH HHS P50 HD103555NIGMS NIH HHS R01 GM132589NINDS NIH HHS R35 NS105078
6 · The paper itself

Abstract

backgroundCopy number variation (CNV) is a class of genomic structural variation (SV) that contributes to genomic disorders and can significantly impact health. Short-read genome sequencing (sr-GS) enables genome-wide SV calling which has been shown to increase diagnosis in unsolved rare disease families. The growing number of large sequencing cohort projects with sr-GS data available requires open free analytical tools that provide visualization of CNV and SV integrated calls associated with gene annotation, proband-parent trio analysis to enable prioritization of de novo variants, B-allele frequency (BAF) plots to support CNV calls, parent of origin assessment and mosaicism detection.

methodsTo support those needs, we developed VizCNV, an open-source platform that incorporates read depth and BAF to enable haplotype-aware CNV analysis. The tool incorporates multiple interactive view modes for SV concurrent calls and annotation tracks for analyzing chromosomal abnormalities [e.g., aneuploidy, segmental aneusomy, and chromosome translocations], gene exonic rearrangements and non-coding gene regulatory regions. In addition, VizCNV includes a built-in filter schema for trio genomes, prioritizing the detection of de novo CNVs. We optimized VizCNV using 1000 Genomes Project data and benchmarked its performance against a cohort containing CNVs validated by multiple technologies. Finally, we applied VizCNV to a molecularly unsolved primary immunodeficiency disease cohort (PIDD, n = 39) previously analyzed by exome sequencing.

resultsUpon computational optimization, VizCNV achieved approximately 82.3% recall and 76.3% precision for deletions > 10 kb. VizCNV accurately detected all 71 validated copy number gains and correctly indicated potential underlying genomic complexities. Haplotype-aware CNV analysis identified a meiosis I non-disjunction event (trisomy 21), three de novo CNVs at two unique loci and 48 inherited candidate CNVs in the PIDD cohort of which 42% (20/48) were validated by integrated CNV/BAF analysis. Moreover, genotype-phenotype analyses revealed that a compound heterozygous combination of a paternal 12.8 kb deletion of exon 5 and a maternal missense variant allele of DOCK8 are the molecular cause of one proband diagnosed with Hyper-IgE syndrome.

conclusionsVizCNV provides a robust and flexible platform for identification of aneuploidies, CNV, SV discovery and visualization of CNV and BAF data. It is also a useful tool to investigate features of genomic rearrangements such as parental origin which has implications for genetic counseling and mechanistic studies. The tool is freely available through https://doi.org/10.6084/m9.figshare.25869523 .

Indexed as

AllelesDNA Copy Number VariationsGenetic Diseases, InbornGenomic Structural VariationPolymorphism, Single NucleotideSoftwareHumansDeletionsDuplicationsGenomic disordersMendelian diseasesRuns of homozygosityStructural variationTrisomy 21

Identifiers

PMID41470026
PMCPMC12866024

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.