Evidence map›Paper›PMID 28911103›Full record

ArticleNucleic acids research2017

Prediction of genome-wide DNA methylation in repetitive elements.

Yinan Zheng, Brian T Joyce, Lei Liu, Zhou Zhang, Warren A Kibbe, Wei Zhang, Lifang Hou

Open access · goldAbstract readValidation Study
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 1 pooled it
6.6field-weighted citation impact, top 2% 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

65 citing papers in PubMed, 1 synthesis or guideline pooled it, 160 citations in OpenAlex.

  1. Pooled it
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  15. Normal gastric tissueEpigenetics reports · 2025
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5 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

7 authors at 3 institutions in 1 country.

Yinan ZhengCenter for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Brian T JoyceCenter for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Lei LiuCenter for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Zhou ZhangCenter for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Warren A KibbeCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD 20850, USA.
Wei ZhangCenter for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Lifang HouCenter for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Northwestern University · USRobert H. Lurie Comprehensive Cancer Center of Northwestern UniversityNational Cancer Institute · US

Funding

Tumor Environment and Metastasis (TEAM) Research ProgramP30CA060553 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI LEONIDAS C. PLATANIAS · 1993 to 2026
$153.9M
Northwestern University Clinical and Translational Science Institute (NUCATS)UL1TR001422 · NCATS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI D'AQUILA, RICHARD · 2015 to 2023
$56.8M
Detection of 5-hmC as a Novel Screening Biomarker for Pancreatic CancerR21CA187869 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI HOU, LIFANG, ZHANG, WEI · 2015 to 2016
$388k
NCATS NIH HHS UL1 TR001422NCI NIH HHS P30 CA060553NCI NIH HHS R21 CA187869
6 · The paper itself

Abstract

DNA methylation in repetitive elements (RE) suppresses their mobility and maintains genomic stability, and decreases in it are frequently observed in tumor and/or surrogate tissues. Averaging methylation across RE in genome is widely used to quantify global methylation. However, methylation may vary in specific RE and play diverse roles in disease development, thus averaging methylation across RE may lose significant biological information. The ambiguous mapping of short reads by and high cost of current bisulfite sequencing platforms make them impractical for quantifying locus-specific RE methylation. Although microarray-based approaches (particularly Illumina's Infinium methylation arrays) provide cost-effective and robust genome-wide methylation quantification, the number of interrogated CpGs in RE remains limited. We report a random forest-based algorithm (and corresponding R package, REMP) that can accurately predict genome-wide locus-specific RE methylation based on Infinium array profiling data. We validated its prediction performance using alternative sequencing and microarray data. Testing its clinical utility with The Cancer Genome Atlas data demonstrated that our algorithm offers more comprehensively extended locus-specific RE methylation information that can be readily applied to large human studies in a cost-effective manner. Our work has the potential to improve our understanding of the role of global methylation in human diseases, especially cancer.

Indexed as

AlgorithmsDNA MethylationGenome, HumanRepetitive Sequences, Nucleic AcidAlu ElementsCpG IslandsFemaleHumansLong Interspersed Nucleotide ElementsMaleNeoplasmsSensitivity and SpecificitySequence Analysis, DNA

Identifiers

PMID28911103
PMCPMC5587781
OpenAlexW2732950170

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.