Evidence map›Paper›PMID 20526417›Full record

ReviewEpigenomics2009

Methods in DNA methylation profiling.

Tao Zuo, Benjamin Tycko, Ta-Ming Liu, Juey-Jen L Lin, Tim H-M Huang

Abstract readReview
In one paragraph

Review in Epigenomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 2 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

36 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  15. Methyl-binding DNA capture Sequencing for Patient Tissues.Journal of visualized experiments : JoVE · 2016
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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

5 authors.

Tao ZuoDivision of Human Cancer Genetics, Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, Ohio State University, Columbus, OH 43210, USA. tim.huang@osumc.edu
Benjamin Tycko
Ta-Ming Liu
Juey-Jen L Lin
Tim H-M Huang

Funding

Epigenomics of Bisphenol A Exposure and Disease RiskR01ES017594 · NIEHS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI HUANG, TIM H.-M. · 2009 to 2013
$1.8M
NIEHS NIH HHS R01 ES017594
6 · The paper itself

Abstract

Metastable and somatically heritable patterns of DNA methylation provide an important level of genomic regulation. In this article, we review methods for analyzing these genome-wide epigenetic patterns and offer a perspective on the ever-expanding literature, which we hope will be useful for investigators who are new to this area. The historical aspects that we cover will be helpful in interpreting this literature and we hope that our discussion of the newest analytical methods will stimulate future progress. We emphasize that no single approach can provide a complete view of the overall methylome, and that combinations of several modalities applied to the same sample set will give the clearest picture. Given the unexpected epigenomic patterns and new biological principles, as well as new disease markers, that have been uncovered in recent studies, it is likely that important discoveries will continue to be made using genome-wide DNA methylation profiling.

Indexed as

AzacitidineBiomarkersChromatography, AffinityDecitabineDNADNA MethylationDNA Modification MethylasesEpigenomicsGene Expression ProfilingMass SpectrometryMicroarray AnalysisSequence Analysis, DNAAzacitidineBiomarkersDecitabineDNADNA Modification Methylasesbisulfite sequencingCpG islanddifferential methylation hybridizationDNA methylationmethylated CpG island recovery assaymethylated DNA immunoprecipitationmethylation profilingmethylation-sensitive SNP chip analysisnext-generation DNA sequencing

Identifiers

PMID20526417
PMCPMC2880494

What OpenQuestion holds

Textmetadata
LicenceTDM
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.