Ontology highlight
ABSTRACT: Background
Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets.Results
As part of the Quartet Project, we establish a publicly available suite of four metabolite reference materials derived from B lymphoblastoid cell lines from a family of parents and monozygotic twin daughters. We generate comprehensive LC-MS-based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. The Quartet multi-sample-based signal-to-noise ratio enables objective assessment of the reliability of intra-batch and cross-batch metabolomics profiling in detecting intrinsic biological differences among the four groups of samples. Significant variations in the reliability of the metabolomics profiling are identified across laboratories. Importantly, ratio-based metabolomics profiling, by scaling the absolute values of a study sample relative to those of a common reference sample, enables cross-laboratory quantitative data integration. Thus, we construct the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory accuracy assessment, which enables objective evaluation of quantitative metabolomics profiling using various instruments and protocols.Conclusions
Our study provides the community with rich resources and best practices for inter-laboratory proficiency tests and data integration, ensuring reliability of large-scale and longitudinal metabolomic studies.
SUBMITTER: Zhang N
PROVIDER: S-EPMC10809448 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Zhang Naixin N Chen Qiaochu Q Zhang Peipei P Zhou Kejun K Liu Yaqing Y Wang Haiyan H Duan Shumeng S Xie Yongming Y Yu Wenxiang W Kong Ziqing Z Ren Luyao L Hou Wanwan W Yang Jingcheng J Gong Xiaoyun X Dong Lianhua L Fang Xiang X Shi Leming L Yu Ying Y Zheng Yuanting Y
Genome biology 20240124 1
<h4>Background</h4>Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets.<h4>Results</h4>As part of the Quartet Project, we establish a publicly available suite of four metabolite reference materials derived from B lymphoblastoid cell lines from a family of parents and monozygotic twin daughters. We generate comprehensive LC-MS-based metabolomic data from the Quartet reference materials using target ...[more]