Evidence map›Paper›PMID 36466778›Full record

ArticleEpigenetics communications2022

Characterization of the Illumina EPIC Array for Optimal Applications in Epigenetic Research Targeting Diverse Human Populations.

Zhou Zhang, Chang Zeng, Wei Zhang

Abstract read
In one paragraph

Article in Epigenetics communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

7 citing papers in PubMed.

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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

3 authors.

Zhou ZhangDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA.
Chang ZengDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA.
Wei ZhangDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA.

Funding

Using epigenomic subtyping to understand the racial differences in lymphomaR21MD011439 · NIMHD · UNIVERSITY OF CHICAGO · PI CHIU, BRIAN C-H, ZHANG, WEI · 2017 to 2018
$455k
NIMHD NIH HHS R21 MD011439
6 · The paper itself

Abstract

The Illumina EPIC array is widely used for high-throughput profiling of DNA cytosine modifications in human samples, covering more than 850,000 modification sites across various genomic features. The application of this platform is expected to provide novel insights into the epigenetic contribution to human complex traits and diseases. Considering the diverse inter-population genetic and epigenetic variation, it will benefit the research community with a comprehensive characterization of this platform for its applicability to major global populations. Specifically, we mapped 866,836 CpG probes from the EPIC array to the human genome reference. We detected 91,034 CpG probes that did not align reliably to the human genome reference. In addition, 21,256 CpG probes were found to ambiguously map to multiple loci in the human genome, and 448 probes showing inaccurate genomic information from the original Illumina annotations. We further characterized those uniquely mapped CpG probes in terms of whether they contained common genetic variants, i.e., single nucleotide polymorphisms (SNPs), in major global populations, by utilizing the 1000 Genomes Project data. A list of optimal CpG probes on the EPIC array was generated for major global populations, with the aim of providing a resource to facilitate future studies of diverse human populations. In conclusion, our analysis indicated that studies of diverse human populations using the EPIC array would be benefited by taking into account of the technical features of this platform.

Indexed as

DNA methylationEpigeneticsmicroarraypopulation epigeneticssingle nucleotide polymorphism

Identifiers

PMID36466778
PMCPMC9718568

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Registered trials

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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.