Article
作者: Huo, Yinbo ; Lin, Ling ; Liang, Xiaozhen ; Chen, Qingwang ; Mai, Yuanbang ; Wang, Haiyan ; Liu, Yaqing ; Hou, Wanwan ; Liu, Gang ; Liu, Ruimei ; Zheng, Yuanting ; Scherer, Andreas ; Yang, Jingcheng ; Wang, Xiaolin ; Shang, Erfei ; Qing, Tao ; Wang, Jing ; Jin, Li ; Xiao, Wenming ; Dong, Lianhua ; Xu, Joshua ; Shao, Li ; Bao, Ding ; Gao, Yuechen ; Sun, Shanyue ; Ren, Luyao ; Wang, Jiucun ; Li, Jingjing ; Zhang, Rui ; Jiang, Hui ; Yu, Ying ; Dai, Fangping ; Tian, Sha ; Zhu, Sibo ; Cao, Chengming ; Chen, Xingdong ; Li, Bingying ; Zhang, Naixin ; Liu, Huafen ; Tong, Weida ; Shang, Jun ; Fang, Xiang ; Zhu, Feng ; Li, Ruiqiang ; Zhang, Ruolan ; Lou, Jingwei ; Ding, Chen ; Cao, Zehui ; Hong, Huixiao ; Han, Jinxiong ; Jiang, He ; Wang, Depeng ; Zhang, Lijun ; Lu, Daru ; Kong, Ziqing ; Lin, Jingchao ; Shi, Leming ; Chen, Qiaochu ; Li, Jinming ; Zhang, Peipei ; Li, Bin
Abstract: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.