Evidence map›Paper›PMID 22986265›Full record

ReviewNature reviews. Genetics2012

Analysing and interpreting DNA methylation data.

Christoph Bock

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 307 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
307citing papers in PubMed, 4 pooled it
–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

307 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Epigenetic regulation and chromatin organization in cystic fibrosis airways.Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society · 2026
    Review
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  10. Uncovering alterations in cancer epigenetics via trans-dimensional Markov chain Monte Carlo and hidden Markov models.Journal of the Royal Statistical Society. Series C, Applied statistics · 2026
    Article
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  20. fSuSiE enables fine-mapping of QTLs from genome-scale molecular profiles.bioRxiv : the preprint server for biology · 2025
    Article

247 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

1 author.

Christoph BockCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria. cbock@cemm.oeaw.ac.at

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation is an epigenetic mark that has suspected regulatory roles in a broad range of biological processes and diseases. The technology is now available for studying DNA methylation genome-wide, at a high resolution and in a large number of samples. This Review discusses relevant concepts, computational methods and software tools for analysing and interpreting DNA methylation data. It focuses not only on the bioinformatic challenges of large epigenome-mapping projects and epigenome-wide association studies but also highlights software tools that make genome-wide DNA methylation mapping more accessible for laboratories with limited bioinformatics experience.

Indexed as

Data Interpretation, StatisticalDNA MethylationAlgorithmsAnimalsBase SequenceDatabases, GeneticData MiningGenetic Association StudiesHumansModels, Biological

Identifiers

PMID22986265

What OpenQuestion holds

Textmetadata
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.