Abstract
Original language | English |
---|---|
Pages (from-to) | 903-914 |
Journal | Nature Biotechnology |
Volume | 32 |
Issue number | 9 |
DOIs | |
Publication status | Published - Sept 2014 |
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In: Nature Biotechnology, Vol. 32, No. 9, 09.2014, p. 903-914.
Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
AU - Su, Zhenqiang
AU - Labaj, Pawel P.
AU - Li, Sheng
AU - Thierry-Mieg, Jean
AU - Thierry-Mieg, Danielle
AU - Shi, Wei
AU - Wang, Charles
AU - Schroth, Gary P.
AU - Setterquist, Robert A.
AU - Thompson, John F.
AU - Jones, Wendell D.
AU - Xiao, Wenzhong
AU - Xu, Weihong
AU - Jensen, Roderick V.
AU - Kelly, Reagan
AU - Xu, Joshua
AU - Conesa, Ana
AU - Furlanello, Cesare
AU - Gao, Hanlin
AU - Hong, Huixiao
AU - Jafari, Nadereh
AU - Letovsky, Stan
AU - Liao, Yang
AU - Lu, Fei
AU - Oakeley, Edward J.
AU - Peng, Zhiyu
AU - Praul, Craig A.
AU - Santoyo-Lopez, Javier
AU - Scherer, Andreas
AU - Shi, Tieliu
AU - Smyth, Gordon K.
AU - Staedtler, Frank
AU - Sykacek, Peter
AU - Tan, Xin-Xing
AU - Thompson, E. Aubrey
AU - Vandesompele, Jo
AU - Wang, May D.
AU - Wang, Jian
AU - Wolfinger, Russell D.
AU - Zavadil, Jiri
AU - Auerbach, Scott S.
AU - Bao, Wenjun
AU - Binder, Hans
AU - Blomquist, Thomas
AU - Brilliant, Murray H.
AU - Bushel, Pierre R.
AU - Cain, Weimin
AU - Catalano, Jennifer G.
AU - Chang, Ching-Wei
AU - Chen, Tao
AU - Chen, Geng
AU - Chen, Rong
AU - Chierici, Marco
AU - Chu, Tzu-Ming
AU - Clevert, Djork-Arne
AU - Deng, Youping
AU - Derti, Adnan
AU - Devanarayan, Viswanath
AU - Dong, Zirui
AU - Dopazo, Joaquin
AU - Du, Tingting
AU - Fang, Hong
AU - Fang, Yongxiang
AU - Fasold, Mario
AU - Fernandez, Anita
AU - Fischer, Matthias
AU - Furio-Tari, Pedro
AU - Fuscoe, James C.
AU - Caiment, Florian
AU - Gaj, Stan
AU - Gandara, Jorge
AU - Gao, Huan
AU - Ge, Weigong
AU - Gondo, Yoichi
AU - Gong, Binsheng
AU - Gong, Meihua
AU - Gong, Zhuolin
AU - Green, Bridgett
AU - Guo, Chao
AU - Guo, Lei
AU - Guo, Li-Wu
AU - Hadfield, James
AU - Hellemans, Jan
AU - Hochreiter, Sepp
AU - Jia, Meiwen
AU - Jian, Min
AU - Johnson, Charles D.
AU - Kay, Suzanne
AU - Kleinjans, Jos
AU - Lababidi, Samir
AU - Levy, Shawn
AU - Li, Quan-Zhen
AU - Li, Li
AU - Li, Peng
AU - Li, Yan
AU - Li, Haiqing
AU - Li, Jianying
AU - Li, Shiyong
AU - Lin, Simon M.
AU - Lopez, Francisco J.
AU - Lu, Xin
AU - Luo, Heng
AU - Ma, Xiwen
AU - Meehan, Joseph
AU - Megherbi, Dalila B.
AU - Mei, Nan
AU - Mu, Bing
AU - Ning, Baitang
AU - Pandey, Akhilesh
AU - Perez-Florido, Javier
AU - Perkins, Roger G.
AU - Peters, Ryan
AU - Phan, John H.
AU - Pirooznia, Mehdi
AU - Qian, Feng
AU - Qing, Tao
AU - Rainbow, Lucille
AU - Rocca-Serra, Philippe
AU - Sambourg, Laure
AU - Sansone, Susanna-Assunta
AU - Schwartz, Scott
AU - Shah, Ruchir
AU - Shen, Jie
AU - Smith, Todd M.
AU - Stegle, Oliver
AU - Stralis-Pavese, Nancy
AU - Stupka, Elia
AU - Suzuki, Yutaka
AU - Szkotnicki, Lee T.
AU - Tinning, Matthew
AU - Tu, Bimeng
AU - van Deft, Joost
AU - Vela-Boza, Alicia
AU - Venturini, Elisa
AU - Walker, Stephen J.
AU - Wan, Liqing
AU - Wang, Wei
AU - Wang, Jinhui
AU - Wang, Jun
AU - Wieben, Eric D.
AU - Willey, James C.
AU - Wu, Po-Yen
AU - Xuan, Jiekun
AU - Yang, Yong
AU - Ye, Zhan
AU - Yin, Ye
AU - Yu, Ying
AU - Yuan, Yate-Ching
AU - Zhang, John
AU - Zhang, Ke K.
AU - Zhang, Wenqian
AU - Zhang, Wenwei
AU - Zhang, Yanyan
AU - Zhao, Chen
AU - Zheng, Yuanting
AU - Zhou, Yiming
AU - Zumbo, Paul
AU - Tong, Weida
AU - Kreil, David P.
AU - Mason, Christopher E.
AU - Shi, Leming
PY - 2014/9
Y1 - 2014/9
N2 - 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.
AB - 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.
U2 - 10.1038/nbt.2957
DO - 10.1038/nbt.2957
M3 - Article
C2 - 25150838
SN - 1087-0156
VL - 32
SP - 903
EP - 914
JO - Nature Biotechnology
JF - Nature Biotechnology
IS - 9
ER -