Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling
Author:
Yu YingORCID, Hou Wanwan, Wang Haiyan, Dong Lianhua, Liu YaqingORCID, Sun Shanyue, Yang Jingcheng, Cao Zehui, Zhang Peipei, Zi Yi, Li Zhihui, Liu Ruimei, Gao Jian, Chen Qingwang, Zhang Naixin, Li Jingjing, Ren LuyaoORCID, Jiang He, Shang Jun, Zhu Sibo, Wang Xiaolin, Qing Tao, Bao Ding, Li Bingying, Li Bin, Suo Chen, Pi Yan, Wang Xia, Dai Fangping, Scherer Andreas, Mattila Pirkko, Han Jingxiong, Zhang Lijun, Jiang Hui, Thierry-Mieg Danielle, Thierry-Mieg Jean, Xiao Wenming, Hong Huixiao, Tong Weida, Wang Jing, Li Jinming, Fang Xiang, Jin Li, Shi LemingORCID, Xu Joshua, Qian Feng, Zhang Rui, Zheng YuantingORCID,
Abstract
AbstractAs an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic 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 using multi-batch RNAseq datasets, providing “ground truth” for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.
Publisher
Cold Spring Harbor Laboratory
Cited by
7 articles.
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