Evidence map›Paper›PMID 38244574›Full record

ArticleBioinformatics (Oxford, England)2024

Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice.

Bjarne Daenekas, Eilís Pérez, Fabio Boniolo, Sabina Stefan, Salvatore Benfatto, Martin Sill, Dominik Sturm, David T W Jones, David Capper, Marc Zapatka and 1 more

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers.

0numbers the graph read from it
0cells of the map it votes in
112citing papers in PubMed
15.7field-weighted citation impact, top 1% of its field
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

112 citing papers in PubMed, 102 citations in OpenAlex.

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  14. Sarcomatous transformation of an astrocytoma IDH-mutant following radiotherapy.Virchows Archiv : an international journal of pathology · 2026
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52 more citing papers are in PubMed but not listed here.

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

11 authors at 3 institutions in 2 countries.

Bjarne DaenekasDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, United States.ORCID 0000-0002-0237-8694
Eilís PérezDepartment of Neuropathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany.
Fabio BonioloDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, United States.
Sabina StefanDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, United States.
Salvatore BenfattoDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, United States.ORCID 0000-0003-4439-3136
Martin SillHopp Children's Cancer Center Heidelberg (KiTZ), 69120 Heidelberg, Germany.ORCID 0000-0001-7616-7665
Dominik SturmHopp Children's Cancer Center Heidelberg (KiTZ), 69120 Heidelberg, Germany.
David T W JonesHopp Children's Cancer Center Heidelberg (KiTZ), 69120 Heidelberg, Germany.
David CapperDepartment of Neuropathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany.ORCID 0000-0003-1945-497X
Marc ZapatkaDivision of Molecular Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.ORCID 0000-0001-8287-5967
Volker HovestadtDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, United States.ORCID 0000-0002-3480-6649
Broad Institute · USGerman Cancer Research Center · DECharité - Universitätsmedizin Berlin · DE

Funding

Berlin School of Integrative OncologyCharles H. Hood FoundationChildren's Cancer Research FundGerman Academic Exchange ServiceStiftung der Deutschen WirtschaftV Foundation
6 · The paper itself

Abstract

motivationCopy-number variations (CNVs) are common genetic alterations in cancer and their detection may impact tumor classification and therapeutic decisions. However, detection of clinically relevant large and focal CNVs remains challenging when sample material or resources are limited. This has motivated us to create a software tool to infer CNVs from DNA methylation arrays which are often generated as part of clinical routines and in research settings.

resultsWe present our R package, conumee 2.0, that combines tangent normalization, an adjustable genomic binning heuristic, and weighted circular binary segmentation to utilize DNA methylation arrays for CNV analysis and mitigate technical biases and batch effects. Segmentation results were validated in a lung squamous cell carcinoma dataset from TCGA (n = 367 samples) by comparison to segmentations derived from genotyping arrays (Pearson's correlation coefficient of 0.91). We further introduce a segmented block bootstrapping approach to detect focal alternations that achieved 60.9% sensitivity and 98.6% specificity for deletions affecting CDKN2A/B (60.0% and 96.9% for RB1, respectively) in a low-grade glioma cohort from TCGA (n = 239 samples). Finally, our tool provides functionality to detect and summarize CNVs across large sample cohorts. AVAILABILITY AND IMPLEMENTATION: Conumee 2.0 is available under open-source license at: https://github.com/hovestadtlab/conumee2.

Indexed as

DNA MethylationNeoplasmsAlgorithmsAnimalsDNA Copy Number VariationsGenomicsHumansMiceSoftware

Identifiers

PMID38244574
PMCPMC10868300
OpenAlexW4391075306

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.