Evidence map›Paper›PMID 36874953›Full record

ArticleBioinformatics advances2023

recountmethylation enables flexible analysis of public blood DNA methylation array data.

Sean K Maden, Brian Walsh, Kyle Ellrott, Kasper D Hansen, Reid F Thompson, Abhinav Nellore

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Sean K MadenComputational Biology Program, Oregon Health & Science University, Portland, OR 97239, USA.ORCID https://orcid.org/0000-0002-2212-4894
Brian WalshComputational Biology Program, Oregon Health & Science University, Portland, OR 97239, USA.ORCID https://orcid.org/0000-0003-0913-1528
Kyle EllrottComputational Biology Program, Oregon Health & Science University, Portland, OR 97239, USA.ORCID https://orcid.org/0000-0002-6573-5900
Kasper D HansenDepartment of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.ORCID https://orcid.org/0000-0003-0086-0687
Reid F ThompsonComputational Biology Program, Oregon Health & Science University, Portland, OR 97239, USA.ORCID https://orcid.org/0000-0003-3661-5296
Abhinav NelloreComputational Biology Program, Oregon Health & Science University, Portland, OR 97239, USA.ORCID https://orcid.org/0000-0001-8145-1484
Oregon Health & Science University · USJohns Hopkins University · US

Funding

Analysis of genomics datasets at a massive scaleR01GM121459 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI HANSEN, KASPER DANIEL · 2017 to 2021
$2.3M
NIGMS NIH HHS R01 GM121459
6 · The paper itself

Abstract

Summary: Thousands of DNA methylation (DNAm) array samples from human blood are publicly available on the Gene Expression Omnibus (GEO), but they remain underutilized for experiment planning, replication and cross-study and cross-platform analyses. To facilitate these tasks, we augmented our recountmethylation R/Bioconductor package with 12 537 uniformly processed EPIC and HM450K blood samples on GEO as well as several new features. We subsequently used our updated package in several illustrative analyses, finding (i) study ID bias adjustment increased variation explained by biological and demographic variables, (ii) most variation in autosomal DNAm was explained by genetic ancestry and CD4+ T-cell fractions and (iii) the dependence of power to detect differential methylation on sample size was similar for each of peripheral blood mononuclear cells (PBMC), whole blood and umbilical cord blood. Finally, we used PBMC and whole blood to perform independent validations, and we recovered 38-46% of differentially methylated probes between sexes from two previously published epigenome-wide association studies. Availability and implementation: Source code to reproduce the main results are available on GitHub (repo: recountmethylation_flexible-blood-analysis_manuscript; url: https://github.com/metamaden/recountmethylation_flexible-blood-analysis_manuscript). All data was publicly available and downloaded from the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/). Compilations of the analyzed public data can be accessed from the website recount.bio/data (preprocessed HM450K array data: https://recount.bio/data/remethdb_h5se-gm_epic_0-0-2_1589820348/; preprocessed EPIC array data: https://recount.bio/data/remethdb_h5se-gm_epic_0-0-2_1589820348/). Supplementary information: Supplementary data are available at

Identifiers

PMID36874953
PMCPMC9976962
OpenAlexW4321370808

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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.