Evidence map›Paper›PMID 31049595›Full record

ArticleNucleic acids research2019

MethylCal: Bayesian calibration of methylation levels.

Eguzkine Ochoa, Verena Zuber, Nora Fernandez-Jimenez, Jose Ramon Bilbao, Graeme R Clark, Eamonn R Maher, Leonardo Bottolo

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 38% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Germline variants inProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  2. Review
  3. Celiac disease: From genetics to epigenetics.World journal of gastroenterology · 2022
    Review
  4. Accurate Measurement of DNA Methylation: Challenges and Bias Correction.Methods in molecular biology (Clifton, N.J.) · 2022
    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 at 3 institutions in 2 countries.

Eguzkine OchoaDepartment of Medical Genetics, University of Cambridge, Cambridge CB2 0QQ, UK.
Verena ZuberDepartment of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK.
Nora Fernandez-JimenezDepartment of Genetics, Physical Anthropology and Animal Physiology, Biocruces-Bizkaia Health Research Institute, University of the Basque Country (UPV/EHU), Leioa, Bizkaia, Spain.
Jose Ramon BilbaoDepartment of Genetics, Physical Anthropology and Animal Physiology, Biocruces-Bizkaia Health Research Institute, University of the Basque Country (UPV/EHU), Leioa, Bizkaia, Spain.
Graeme R ClarkDepartment of Medical Genetics, University of Cambridge, Cambridge CB2 0QQ, UK.
Eamonn R MaherDepartment of Medical Genetics, University of Cambridge, Cambridge CB2 0QQ, UK.
Leonardo BottoloDepartment of Medical Genetics, University of Cambridge, Cambridge CB2 0QQ, UK.
University of Cambridge · GBUniversity of the Basque Country · ESTuring Institute · GB

Funding

Medical Research Council MC_UU_00002/7Medical Research Council MR/S019669/1
6 · The paper itself

Abstract

Bisulfite amplicon sequencing has become the primary choice for single-base methylation quantification of multiple targets in parallel. The main limitation of this technology is a preferential amplification of an allele and strand in the PCR due to methylation state. This effect, known as 'PCR bias', causes inaccurate estimation of the methylation levels and calibration methods based on standard controls have been proposed to correct for it. Here, we present a Bayesian calibration tool, MethylCal, which can analyse jointly all CpGs within a CpG island (CGI) or a Differentially Methylated Region (DMR), avoiding 'one-at-a-time' CpG calibration. This enables more precise modeling of the methylation levels observed in the standard controls. It also provides accurate predictions of the methylation levels not considered in the controlled experiment, a feature that is paramount in the derivation of the corrected methylation degree. We tested the proposed method on eight independent assays (two CpG islands and six imprinting DMRs) and demonstrated its benefits, including the ability to detect outliers. We also evaluated MethylCal's calibration in two practical cases, a clinical diagnostic test on 18 patients potentially affected by Beckwith-Wiedemann syndrome, and 17 individuals with celiac disease. The calibration of the methylation levels obtained by MethylCal allows a clearer identification of patients undergoing loss or gain of methylation in borderline cases and could influence further clinical or treatment decisions.

Indexed as

Bayes TheoremDNA MethylationGenomic ImprintingAlgorithmsBeckwith-Wiedemann SyndromeCalibrationCeliac DiseaseComputational BiologyCpG IslandsHumansPotassium Channels, Voltage-GatedReproducibility of ResultsRNA, Long NoncodingSensitivity and SpecificitySequence Analysis, DNAH19 long non-coding RNAKCNQ1OT1 long non-coding RNA, humanPotassium Channels, Voltage-GatedRNA, Long Noncoding

Identifiers

PMID31049595
PMCPMC6698668
OpenAlexW2950437876

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.