A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

RNA序列 计算生物学 基因表达谱 核糖核酸 生物 DNA微阵列 基因 基因表达 遗传学 转录组
作者
Zhenqiang Su,Paweł P. Łabaj,Sheng Li,Jean Thierry‐Mieg,Danielle Thierry‐Mieg,Wei Shi,Charles Wang,Gary P. Schroth,Robert A. Setterquist,John F. Thompson,Wendell Jones,Wenzhong Xiao,Weihong Xu,Roderick V. Jensen,Reagan Kelly,Joshua Xu,Ana Conesa,Cesare Furlanello,Hanlin Gao,Huixiao Hong,Nadereh Jafari,Stan Letovsky,Yang Liao,Fei Lü,Edward J. Oakeley,Zhiyu Peng,Craig A. Praul,Javier Santoyo‐López,Andreas Scherer,Tieliu Shi,Gordon K. Smyth,Frank Staedtler,Peter Sykacek,Xin Xing Tan,E. Aubrey Thompson,Jo Vandesompele,May D. Wang,Jian Wang,Russell D. Wolfinger,Jiří Zavadil,Scott S. Auerbach,Wenjun Bao,Hans Binder,Thomas Blomquist,Murray H. Brilliant,Pierre R. Bushel,Weimin Cai,Jennifer Catalano,Ching Wei Chang,Tao Chen,Geng Chen,Rong Chen,Marco Chierici,Tzu Ming Chu,Djork-Arné Clevert,Youping Deng,Adnan Derti,Viswanath Devanarayan,Zirui Dong,Joaquı́n Dopazo,Tingting Du,Hong Fang,Yongxiang Fang,Mario Fasold,Anita Fernandez,Matthias Fischer,Pedro Furió‐Tarí,James C. Fuscoe,Florian Caimet,Stan Gaj,Jorge Gandara,Huan Gao,Weigong Ge,Yoichi Gondo,Binsheng Gong,Meihua Gong,Zhuolin Gong,Bridgett Green,Chao Guo,Lei Guo,Li Guo,James Hadfield,Jan Hellemans,Sepp Hochreiter,Meiwen Jia,Min Jian,Charles D. Johnson,Suzanne Kay,Jos Kleinjans,Samir Lababidi,Shawn Levy,Quan Zhen Li,Li Li,Peng Li,Yan Li,Haiqing Li,Jianying Li,Shiyong Li,Simon Lin,Francisco J. López,Xin Lü,Heng Luo,Xiwen Ma,Joe Meehan,Dalila B. Megherbi,Nan Mei,Bing Mu,Baitang Ning,Akhilesh Pandey,Javier Pérez-Florido,Roger Perkins,Ryan Peters,John H. Phan,Mehdi Pirooznia,Feng Qian,Tao Qing,Lucille Rainbow,Philippe Rocca-Serra,Laure Sambourg,Susanna‐Assunta Sansone,Scott Schwartz,Ruchir Shah,Jie Shen,T. M. F. Smith,Oliver Stegle,Nancy Stralis‐Pavese,Elia Stupka,Yutaka Suzuki,Lee T. Szkotnicki,Matthew Tinning,Bimeng Tu,Joost van Delft,Alicia Vela‐Boza,Elisa Venturini,Stephen J. Walker,Liqing Wan,Wei Wang,Jinhui Wang,Jun Wang,Eric D. Wieben,James C. Willey,Po Yen Wu,Jiekun Xuan,Yang Liao,Zhan Ye,Ye Yin,Ying Yu,Yate Ching Yuan,John H. Zhang,Ke K. Zhang,Wenqian Zhang,Wen‐Wei Zhang,Yanyan Zhang,Chen Zhao,Yuanting Zheng,Yiming Zhou,Paul Zumbo,Weida Tong,David P. Kreil,Christopher E. Mason,Leming Shi
出处
期刊:Nature Biotechnology [Springer Nature]
卷期号:32 (9): 903-914 被引量:949
标识
DOI:10.1038/nbt.2957
摘要

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.
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