Evidence map›Paper›PMID 37337720›Full record

ArticleEpigenomics2023

Calculating detection limits and uncertainty of reference-based deconvolution of whole-blood DNA methylation data.

Shelby Bell-Glenn, Lucas A Salas, Annette M Molinaro, Rondi A Butler, Brock C Christensen, Karl T Kelsey, John K Wiencke, Devin C Koestler

Abstract read
In one paragraph

Article in Epigenomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

8 authors.

Shelby Bell-GlennDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA.
Lucas A SalasDepartment of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH 03756, USA.
Annette M MolinaroDepartment of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.
Rondi A ButlerDepartments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA.
Brock C ChristensenDepartment of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH 03756, USA.
Karl T KelseyDepartments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA.
John K WienckeDepartment of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.
Devin C KoestlerDepartment of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA.ORCID 0000-0002-0598-0146

Funding

Mentoring CoreP20GM103418 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Douglas E Wright · 2012 to 2026
$63.0M
Tissue CoreP50CA097257 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Joseph F Costello · 2002 to 2026
$57.4M
Transgenic & Gene-Targeting Shared ResourceP30CA168524 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI ROY A. JENSEN · 2012 to 2026
$40.1M
Using Integrated Omics to Identify Dysfunctional Genetic Mechanisms Influencing Schizophrenia and Sleep DisturbancesP20GM130423 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Diane E Mahoney · 2019 to 2026
$21.5M
Immune epigenetic biomarkers of survival in glioma epidemiologyR01CA207360 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WIENCKE, JOHN K. · 2017 to 2021
$3.8M
NCI NIH HHS P30 CA168524NCI NIH HHS P50 CA097257NCI NIH HHS R01 CA207360NIGMS NIH HHS P20 GM103418NIGMS NIH HHS P20 GM103418, P20 GM130423NIGMS NIH HHS P20 GM130423
6 · The paper itself

Abstract

DNA methylation (DNAm)-based cell mixture deconvolution (CMD) has become a quintessential part of epigenome-wide association studies where DNAm is profiled in heterogeneous tissue types. Despite being introduced over a decade ago, detection limits, which represent the smallest fraction of a cell type in a mixed biospecimen that can be reliably detected, have yet to be determined in the context of DNAm-based CMD. Moreover, there has been little attention given to approaches for quantifying the uncertainty associated with DNAm-based CMD. Here, analytical frameworks for determining both cell-specific limits of detection and quantification of uncertainty associated with DNAm-based CMD are described. This work may contribute to improved rigor, reproducibility and replicability of epigenome-wide association studies involving CMD.

Indexed as

DNA MethylationEpigenesis, GeneticHumansLimit of DetectionReproducibility of ResultsUncertaintycellular deconvolutionDNA methylationEWASin silico mixtureslimit of blanklimit of detection

Identifiers

PMID37337720
PMCPMC10308256

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.