Quartet metabolite reference materials for assessing inter-laboratory reliability and data integration of metabolomic profiling

Zhang, Naixin; Zhang, Peipei; Chen, Qiaochu; Zhou, Kejun; Liu, Yaqing; Wang, Haiyan; Xie, Yongming; Ren, Luyao; Hou, Wanwan; Yang, Jingcheng; Yu, Ying; Zheng, Yuanting; Shi, Leming

doi:10.1101/2022.11.01.514762

Cited by 12 publications

(4 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2). Four accompanying papers detail the establishment of the DNA 66 , RNA 67 , protein 68 and metabolite 69 reference materials, reference datasets and QC methods for each type of omics profiling. Haplotype-resolved assemblies and a variant benchmark have also been provided 70 .…”

Section: Articlementioning

confidence: 99%

See 1 more Smart Citation

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Zheng,

Liu,

Yang

et al. 2023

Nat Biotechnol

Self Cite

View full text Add to dashboard Cite

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free ‘absolute’ feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

show abstract

Section: Articlementioning

confidence: 99%

“…Targeted metabolomics datasets were generated using Waters Xevo TQ-S, AB Sciex QTRAP 5500 and AB Sciex QTRAP 6500+ mass spectrometers in four labs. More information is provided in the accompanying paper on metabolites 69 .…”

Section: Mass Spectrometry-based Metabolomics Datamentioning

confidence: 99%

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Zheng,

Liu,

Yang

et al. 2023

Nat Biotechnol

Self Cite

View full text Add to dashboard Cite

show abstract

“…Importantly, the RNA reference materials have been approved by China's State Administration for Market Regulation as the First Class of National Reference Materials and are extensively being utilized for proficiency testing and method validation. Furthermore, matched multiomics reference materials including DNAs 26 , proteins 27 and metabolites 28 were established along with RNAs from the same culturing of the immortalized cell lines (see accompanying manuscripts). The comprehensive set of multiomics reference materials enables cross-omics validations and performance assessment at multiomics integration level 29 .…”

Section: Introductionmentioning

confidence: 99%

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

Hou

Wang

et al. 2022

Preprint

View full text Add to dashboard Cite

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications such as companion diagnostics and prognostics. However, there is a lack of certified RNA reference materials and the corresponding reference datasets of differential expression for assessing the reliability of RNAseq for its intended use in detecting intrinsically small biological differences in clinical settings such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multiomics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two reference samples, providing "ground truth" for cross-platform and cross-lab proficiency test. Moreover, Quartet-sample-based quality metrics were developed for assessing the reliability of RNAseq technology in terms of intra-batch measurement and cross-batch data integration. The small intrinsic biological differences among the Quartet samples enabled sensitive assessment of performance of transcriptomic measurements and their cross-batch integration at the ratio level. The Quartet RNA reference materials combined with the ratio-based reference datasets can serve as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

show abstract

“…The targeted metabolomics datasets were generated using Waters Xevo TQ-S, AB SCIEX QTRAP 5500, and AB SCIEX QTRAP 6500+ mass spectrometers in four labs. More information was detailed in the metabolite accompanying paper(Zhang et al, 2022).…”

mentioning

confidence: 99%

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Zheng

Liu

Yang

et al. 2022

Preprint

View full text Add to dashboard Cite

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

show abstract

Quartet metabolite reference materials for assessing inter-laboratory reliability and data integration of metabolomic profiling

Cited by 12 publications

References 54 publications

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Contact Info

Product

Resources

About