Evidence map›Paper›PMID 34728774›Full record

ArticleCommunications biology2021

Charting differentially methylated regions in cancer with Rocker-meth.

Matteo Benelli, Gian Marco Franceschini, Alberto Magi, Dario Romagnoli, Chiara Biagioni, Ilenia Migliaccio, Luca Malorni, Francesca Demichelis

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 27% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
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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

8 authors at 3 institutions in 2 countries.

Matteo Benelli *Bioinformatics Unit, Hospital of Prato, Prato, Italy. matteo.benelli@uslcentro.toscana.it.ORCID 0000-0003-1227-356X
Gian Marco Franceschini *Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy.ORCID 0000-0002-7391-3535
Alberto MagiDepartment of Information Engineering, University of Florence, Florence, Italy.ORCID 0000-0001-7393-4283
Dario RomagnoliBioinformatics Unit, Hospital of Prato, Prato, Italy.
Chiara BiagioniBioinformatics Unit, Hospital of Prato, Prato, Italy.ORCID 0000-0002-7908-4854
Ilenia Migliaccio"Sandro Pitigliani" Translational Research Unit, Hospital of Prato, Prato, Italy.
Luca Malorni"Sandro Pitigliani" Medical Oncology Department, Hospital of Prato, Prato, Italy.ORCID 0000-0002-4297-2997
Francesca DemichelisDepartment of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy. f.demichelis@unitn.it.ORCID 0000-0002-8266-8631
Hospital of Prato · ITUniversity of Trento · ITUniversity of Florence · IT

Funding

Weill Cornell Medicine (WCM) SPORE in Prostate CancerP50CA211024 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI LODA, MASSIMO · 2017 to 2021
$10.9M
Ministry of Health, Italy | Agenzia Italiana del Farmaco, Ministero della Salute (Italian Medicines Agency) GR-2018-12365195NCI NIH HHS P50 CA211024
6 · The paper itself

Abstract

Differentially DNA methylated regions (DMRs) inform on the role of epigenetic changes in cancer. We present Rocker-meth, a new computational method exploiting a heterogeneous hidden Markov model to detect DMRs across multiple experimental platforms. Through an extensive comparative study, we first demonstrate Rocker-meth excellent performance on synthetic data. Its application to more than 6,000 methylation profiles across 14 tumor types provides a comprehensive catalog of tumor type-specific and shared DMRs, and agnostically identifies cancer-related partially methylated domains (PMD). In depth integrative analysis including orthogonal omics shows the enhanced ability of Rocker-meth in recapitulating known associations, further uncovering the pan-cancer relationship between DNA hypermethylation and transcription factor deregulation depending on the baseline chromatin state. Finally, we demonstrate the utility of the catalog for the study of colorectal cancer single-cell DNA-methylation data.

Indexed as

DNA MethylationEpigenesis, GeneticComputational BiologyHumansMarkov ChainsNeoplasms

Identifiers

PMID34728774
PMCPMC8563962
OpenAlexW3208183603

What OpenQuestion holds

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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.