Evidence map›Paper›PMID 39723231›Full record

ReviewPhenomics (Cham, Switzerland)2024

Reference Materials for Improving Reliability of Multiomics Profiling.

Luyao Ren, Leming Shi, Yuanting Zheng

Abstract readReview
In one paragraph

Review in Phenomics (Cham, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 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.

Luyao RenState Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, 200438 China.ORCID 0000-0002-4052-1148
Leming ShiState Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, 200438 China.ORCID 0000-0002-2981-4150
Yuanting ZhengState Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, 200438 China.ORCID 0000-0003-4480-8303

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-throughput technologies for multiomics or molecular phenomics profiling have been extensively adopted in biomedical research and clinical applications, offering a more comprehensive understanding of biological processes and diseases. Omics reference materials play a pivotal role in ensuring the accuracy, reliability, and comparability of laboratory measurements and analyses. However, the current application of omics reference materials has revealed several issues, including inappropriate selection and underutilization, leading to inconsistencies across laboratories. This review aims to address these concerns by emphasizing the importance of well-characterized reference materials at each level of omics, encompassing (epi-)genomics, transcriptomics, proteomics, and metabolomics. By summarizing their characteristics, advantages, and limitations along with appropriate performance metrics pertinent to study purposes, we provide an overview of how omics reference materials can enhance data quality and data integration, thus fostering robust scientific investigations with omics technologies.

Indexed as

Molecular phenomicsMultiomics profilingPerformance metricsQuality controlReference datasetsReference materialsReproducibility

Identifiers

PMID39723231
PMCPMC11666855

What OpenQuestion holds

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LicenceCC BY
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.