Sci Data January 2023 PMID 36720882

Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants.

Scott C Ritchie, Praveen Surendran, Savita Karthikeyan, Samuel A Lambert, Thomas Bolton, Lisa Pennells, John Danesh, Emanuele Di Angelantonio, Adam S Butterworth, Michael Inouye

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Mentions

Peak: 2 in Sep 2021

across 2 sources since Sep 2021

Extended reach

54,351

potential audience

Total likes

Video views

Mentions per month

Sep 2021 – May 2023

Where it's discussed

X / Twitter4 posts
YouTube1 videos

AI synopsis

What people are saying

Discussions reflect a balanced appreciation for the research, with posts highlighting the importance of technical control and new tools such as ukbnmr, using words like 'significant' and 'valuable' to underscore their potential impact. The tone blends technical acknowledgment with recognition of the importance for future studies, demonstrating moderate engagement and perceived influence.

AgreementModerate agreement

Most discussions acknowledge the significance of the publication, with some explicitly supporting the methods and findings.

InterestModerate interest

Participants show moderate curiosity about the technical aspects and implications of the study, engaging with the topic without overwhelming enthusiasm.

EngagementModerate engagement

Comments include mentions of specific tools like ukbnmr, references to data quality improvements, and some technical dialogue, indicating a moderate level of in-depth interaction.

ImpactModerate impact

The collective tone suggests that the publication’s advancements could notably influence future research practices and data handling, highlighting its relevance.

Abstract in brief

The study focuses on identifying and correcting technical variations in NMR metabolic biomarker data from around 120,000 UK Biobank participants, which can affect the accuracy of research findings.
Sources of unwanted variation such as sample preparation time, shipping, batch effects, and spectrometer drift were identified and addressed to improve data quality.
An R software tool called ukbnmr was developed to help researchers remove these technical issues, making the data more reliable for genetic and epidemiological studies.

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All mentions

Enhancing NMR Biomarker Data Quality in UK Biobank Using R Tool

This video discusses methods to identify and correct technical variations in NMR metabolic biomarker data from 120,000 UK Biobank participants, improving data reliability for genetic and epidemiological research. The…

STEM RTCL TV · May 19, 2023 21 views

Scientific Data

@ScientificData · X

RT @nmr900: . @ScientificData (open) Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biob…

Feb 2, 2023 · 1 share · 24,630 followers View post →

Magnetic Resonance News

@nmr900 · X

Jan 31, 2023 · 1 like · 1 share · 6,113 followers View post →

Magnetic Resonance News

@nmr900 · X

RT @medrxivpreprint: Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants…

Sep 27, 2021 · 1 share · 6,113 followers View post →

medRxiv

@medrxivpreprint · X

Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants https://t.co/TaUk80wndF #medRxiv

Sep 27, 2021 · 1 share · 17,466 followers View post →