Evidence map›Paper›PMID 26786415›Full record

ArticleEpigenetics2016

Comparison of Methyl-capture Sequencing vs. Infinium 450K methylation array for methylome analysis in clinical samples.

Ai Ling Teh, Hong Pan, Xinyi Lin, Yubin Ives Lim, Chinari Pawan Kumar Patro, Clara Yujing Cheong, Min Gong, Julia L MacIsaac, Chee-Keong Kwoh, Michael J Meaney and 5 more

Abstract readComparative Study
In one paragraph

Article in Epigenetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 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

40 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

15 authors.

Ai Ling Teha Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Hong Pana Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Xinyi Lina Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Yubin Ives Lima Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Chinari Pawan Kumar Patroa Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Clara Yujing Cheonga Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Min Gonga Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Julia L MacIsaace Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute , Department of Medical Genetics , University of British Columbia , Vancouver , BC , Canada.
Chee-Keong Kwohb School of Computer Engineering, Nanyang Technological University , Singapore.
Michael J Meaneya Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Michael S Kobore Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute , Department of Medical Genetics , University of British Columbia , Vancouver , BC , Canada.
Yap-Seng Chonga Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Peter D Gluckmana Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Joanna D Holbrooka Singapore Institute for Clinical Sciences, A*STAR , Singapore.
Neerja Karnania Singapore Institute for Clinical Sciences, A*STAR , Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interindividual variability in the epigenome has gained tremendous attention for its potential in pathophysiological investigation, disease diagnosis, and evaluation of clinical intervention. DNA methylation is the most studied epigenetic mark in epigenome-wide association studies (EWAS) as it can be detected from limited starting material. Infinium 450K methylation array is the most popular platform for high-throughput profiling of this mark in clinical samples, as it is cost-effective and requires small amounts of DNA. However, this method suffers from low genome coverage and errors introduced by probe cross-hybridization. Whole-genome bisulfite sequencing can overcome these limitations but elevates the costs tremendously. Methyl-Capture Sequencing (MC Seq) is an attractive intermediate solution to increase the methylome coverage in large sample sets. Here we first demonstrate that MC Seq can be employed using DNA amounts comparable to the amounts used for Infinium 450K. Second, to provide guidance when choosing between the 2 platforms for EWAS, we evaluate and compare MC Seq and Infinium 450K in terms of coverage, technical variation, and concordance of methylation calls in clinical samples. Last, since the focus in EWAS is to study interindividual variation, we demonstrate the utility of MC Seq in studying interindividual variation in subjects from different ethnicities.

Indexed as

DNA MethylationEpigenesis, GeneticEthnicityFemaleGenome, HumanHumansMaleOligonucleotide Array Sequence AnalysisSequence AlignmentSequence Analysis, DNADNA methylationEpigenome-wide association studyInfinium HumanMethylation450 arrayMethyl-Capture Sequencingnext generation sequencing

Identifiers

PMID26786415
PMCPMC4846133

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.