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