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Quartet RNA reference materials improve the quality of transcriptomic data through ratio-based profiling.

Ying YuWanwan HouYa-Qing LiuHaiyan WangLianhua DongYuanbang MaiQing-Wang ChenZhihui LiShanyue SunJingcheng YangZehui CaoPeipei ZhangYi ZiRuimei LiuJian GaoNaixin ZhangJing-Jing LiLuyao RenHe JiangJun ShangSibo ZhuXiaolin WangTao QingDing BaoBingying LiBin LiChen SuoYan PiXia WangFangping DaiAndreas SchererPirkko MattilaJinxiong HanLijun ZhangHui JiangDanielle Thierry-MiegJean Thierry-MiegWenming XiaoHuixiao HongWeida TongJing WangJinming LiXiang FangLi JinJoshua XuFeng QianRui ZhangLe-Ming ShiYuanting Zheng
Published in: Nature biotechnology (2023)
Certified RNA reference materials are indispensable for assessing the reliability of RNA sequencing to detect 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 multi-omics 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 samples, providing cross-platform and cross-laboratory 'ground truth'. Investigation of the intrinsically subtle biological differences among the Quartet samples enables sensitive assessment of cross-batch integration of transcriptomic measurements at the ratio level. The Quartet RNA reference materials, combined with the ratio-based reference datasets, can serve as unique resources for assessing and improving the quality of transcriptomic data in clinical and biological settings.
Keyphrases
  • single cell
  • rna seq
  • electronic health record
  • quality control
  • big data
  • quality improvement
  • nucleic acid
  • wastewater treatment
  • machine learning
  • dna methylation
  • artificial intelligence
  • data analysis