Evidence map›Paper›PMID 42178371›Full record

ArticleBioinformatics (Oxford, England)2026

MarkerMatch: a proximity-based probe-matching algorithm for joint analysis of copy-number variants from different genotyping arrays.

Franjo Ivankovic, Dongmei Yu, James Shen, Lingyu Zhan, Maria Niarchou, Ariadne Kaylor, Laura Domènech, Tyne W Miller-Fleming, Luz M Porras, Paola Giusti-Rodríguez and 3 more

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Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Franjo IvankovicDepartment of Psychiatry, Center for OCD, Anxiety, and Related Disorders, McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL 32603, United States.ORCID 0000-0002-6776-8626
Dongmei YuStanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States.ORCID 0000-0001-7901-4365
James ShenDepartment of Psychiatry, Center for OCD, Anxiety, and Related Disorders, McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL 32603, United States.ORCID 0009-0007-3406-3025
Lingyu ZhanCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90024, United States.ORCID 0000-0001-6718-878X
Maria NiarchouDivision of Genetic Medicine and Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37240, United States.ORCID 0000-0002-8855-7393
Ariadne KaylorPsychiatric and Neurodevelopmental Genetics Unit, Departments of Psychiatry and Neurology, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, United States.ORCID 0009-0003-9576-8679
Laura DomènechStanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States.ORCID 0000-0003-2265-0824
Tyne W Miller-FlemingDivision of Genetic Medicine and Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37240, United States.ORCID 0000-0002-0398-5162
Luz M PorrasDepartment of Psychiatry, Center for OCD, Anxiety, and Related Disorders, McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL 32603, United States.ORCID 0000-0002-0162-4494
Paola Giusti-RodríguezDepartment of Psychiatry, Center for OCD, Anxiety, and Related Disorders, McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL 32603, United States.ORCID 0000-0002-1921-1305
Roel A OphoffCenter for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90024, United States.ORCID 0000-0002-8287-6457
Jeremiah M ScharfStanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States.ORCID 0000-0002-4742-5896
Carol A MathewsDepartment of Psychiatry, Center for OCD, Anxiety, and Related Disorders, McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL 32603, United States.ORCID 0000-0003-2208-7058

Funding

Interdisciplinary Training in Movement Disorders and NeurorestorationT32NS082168 · NINDS · UNIVERSITY OF FLORIDA · PI Melissa Jo Armstrong, David E Vaillancourt · 2015 to 2026
$2.8M
National Institute for Neurological Disorders and Stroke NS082168NINDS NIH HHS T32 NS082168
6 · The paper itself

Abstract

motivationCopy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to detect CNVs, which can be used in genetic association tests. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (those present on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has led to excessive reduction in overall sensitivity since arrays can have an undesirably low probe overlap. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision.

resultsBy analyzing CNV calls from 4906 individuals genotyped across three different arrays, we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g. use of consensus probes only). We further demonstrate that MarkerMatch matches the CNV detection from current practice in terms of F1 score and PPV for larger CNVs. We also optimize MarkerMatch parameters, DMAX and Method, and find an optimal DMAX setting at 10 kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis. AVAILABILITY: The R package for MarkerMatch is available at: https://github.com/FranjoIM/MarkerMatch. The code used for analysis and implementation is available at: https://doi.org/10.5281/zenodo.18460979. The live notebook is available at https://fivankovic.notion.site/2026-markermatch.

Indexed as

AlgorithmsDNA Copy Number VariationsGenotyping TechniquesOligonucleotide Array Sequence AnalysisSoftwareGenotypeHumans

Identifiers

PMID42178371
PMCPMC13257853

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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.