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

(2014) NATURE BIOTECHNOLOGY. 32(9). p.903-914
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Abstract
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.
Keywords
GENOME ANNOTATION, GENE-EXPRESSION ANALYSIS, ARRAYS, TRANSCRIPTOME, CALIBRATION, ALIGNER, PROJECT, CELLS, BIAS, PCR

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MLA
Su, Zhenqiang et al. “A Comprehensive Assessment of RNA-seq Accuracy, Reproducibility and Information Content by the Sequencing Quality Control Consortium.” NATURE BIOTECHNOLOGY 32.9 (2014): 903–914. Print.
APA
Su, Z., Labaj, P. P., Li, S., Thierry-Mieg, J., Thierry-Mieg, D., Shi, W., Wang, C., et al. (2014). A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium. NATURE BIOTECHNOLOGY, 32(9), 903–914.
Chicago author-date
Su, Zhenqiang, Pawel P Labaj, Sheng Li, Jean Thierry-Mieg, Danielle Thierry-Mieg, Wei Shi, Charles Wang, et al. 2014. “A Comprehensive Assessment of RNA-seq Accuracy, Reproducibility and Information Content by the Sequencing Quality Control Consortium.” Nature Biotechnology 32 (9): 903–914.
Chicago author-date (all authors)
Su, Zhenqiang, Pawel P Labaj, Sheng Li, Jean Thierry-Mieg, Danielle Thierry-Mieg, Wei Shi, Charles Wang, Gary P Schroth, Robert A Setterquist, John F Thompson, Wendell D 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 Lu, Edward J Oakeley, Zhiyu Peng, Craig A Praul, Javier Santoyo-Lopez, 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, Jiri Zavadil, Scott S Auerbach, Wenjun Bao, Hans Binder, Thomas Blomquist, Murray H Brilliant, Pierre R Bushel, Weimin Cain, Jennifer G 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, Joaquin Dopazo, Tingting Du, Hong Fang, Yongxiang Fang, Mario Fasold, Anita Fernandez, Matthias Fischer, Pedro Furió-Tari, 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-Wu 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, Li Li, Peng Li, Yan Li, Haiqing Li, Jianying Li, Shiyong Li, Simon M Lin, Francisco J López, Xin Lu, Heng Luo, Xiwen Ma, Joseph Meehan, Dalila B Megherbi, Nan Mei, Bing Mu, Baitang Ning, Akhilesh Pandey, Javier Pérez-Florido, Roger G 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, Todd M Smith, Oliver Stegle, Nancy Stralis-Pavese, Elia Stupka, Yutaka Suzuki, Lee T Szkotnicki, Matthew Tinning, Bimeng Tu, Joost van Deft, 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, Yong Yang, Zhan Ye, Ye Yin, Ying Yu, Yate-Ching Yuan, John Zhang, Ke K Zhang, Wenqian Zhang, Wenwei Zhang, Yanyan Zhang, Chen Zhao, Yuanting Zheng, Yiming Zhou, Paul Zumbo, Weida Tong, David P Kreil, Christopher E Mason, and Leming Shi. 2014. “A Comprehensive Assessment of RNA-seq Accuracy, Reproducibility and Information Content by the Sequencing Quality Control Consortium.” Nature Biotechnology 32 (9): 903–914.
Vancouver
1.
Su Z, Labaj PP, Li S, Thierry-Mieg J, Thierry-Mieg D, Shi W, et al. A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium. NATURE BIOTECHNOLOGY. 2014;32(9):903–14.
IEEE
[1]
Z. Su et al., “A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium,” NATURE BIOTECHNOLOGY, vol. 32, no. 9, pp. 903–914, 2014.
@article{6844316,
  abstract     = {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.},
  author       = {Su, Zhenqiang and Labaj, Pawel P and Li, Sheng and Thierry-Mieg, Jean and Thierry-Mieg, Danielle and Shi, Wei and Wang, Charles and Schroth, Gary P and Setterquist, Robert A and Thompson, John F and Jones, Wendell D and Xiao, Wenzhong and Xu, Weihong and Jensen, Roderick V and Kelly, Reagan and Xu, Joshua and Conesa, Ana and Furlanello, Cesare and Gao, Hanlin and Hong, Huixiao and Jafari, Nadereh and Letovsky, Stan and Liao, Yang and Lu, Fei and Oakeley, Edward J and Peng, Zhiyu and Praul, Craig A and Santoyo-Lopez, Javier and Scherer, Andreas and Shi, Tieliu and Smyth, Gordon K and Staedtler, Frank and Sykacek, Peter and Tan, Xin-Xing and Thompson, E Aubrey and Vandesompele, Jo and Wang, May D and Wang, Jian and Wolfinger, Russell D and Zavadil, Jiri and Auerbach, Scott S and Bao, Wenjun and Binder, Hans and Blomquist, Thomas and Brilliant, Murray H and Bushel, Pierre R and Cain, Weimin and Catalano, Jennifer G and Chang, Ching-Wei and Chen, Tao and Chen, Geng and Chen, Rong and Chierici, Marco and Chu, Tzu-Ming and Clevert, Djork-Arné and Deng, Youping and Derti, Adnan and Devanarayan, Viswanath and Dong, Zirui and Dopazo, Joaquin and Du, Tingting and Fang, Hong and Fang, Yongxiang and Fasold, Mario and Fernandez, Anita and Fischer, Matthias and Furió-Tari, Pedro and Fuscoe, James C and Caimet, Florian and Gaj, Stan and Gandara, Jorge and Gao, Huan and Ge, Weigong and Gondo, Yoichi and Gong, Binsheng and Gong, Meihua and Gong, Zhuolin and Green, Bridgett and Guo, Chao and Guo, Lei and Guo, Li-Wu and Hadfield, James and Hellemans, Jan and Hochreiter, Sepp and Jia, Meiwen and Jian, Min and Johnson, Charles D and Kay, Suzanne and Kleinjans, Jos and Lababidi, Samir and Levy, Shawn and Li, Quan-Zhen and Li, Li and Li, Li and Li, Peng and Li, Yan and Li, Haiqing and Li, Jianying and Li, Shiyong and Lin, Simon M and López, Francisco J and Lu, Xin and Luo, Heng and Ma, Xiwen and Meehan, Joseph and Megherbi, Dalila B and Mei, Nan and Mu, Bing and Ning, Baitang and Pandey, Akhilesh and Pérez-Florido, Javier and Perkins, Roger G and Peters, Ryan and Phan, John H and Pirooznia, Mehdi and Qian, Feng and Qing, Tao and Rainbow, Lucille and Rocca-Serra, Philippe and Sambourg, Laure and Sansone, Susanna-Assunta and Schwartz, Scott and Shah, Ruchir and Shen, Jie and Smith, Todd M and Stegle, Oliver and Stralis-Pavese, Nancy and Stupka, Elia and Suzuki, Yutaka and Szkotnicki, Lee T and Tinning, Matthew and Tu, Bimeng and van Deft, Joost and Vela-Boza, Alicia and Venturini, Elisa and Walker, Stephen J and Wan, Liqing and Wang, Wei and Wang, Jinhui and Wang, Jun and Wieben, Eric D and Willey, James C and Wu, Po-Yen and Xuan, Jiekun and Yang, Yong and Ye, Zhan and Yin, Ye and Yu, Ying and Yuan, Yate-Ching and Zhang, John and Zhang, Ke K and Zhang, Wenqian and Zhang, Wenwei and Zhang, Yanyan and Zhao, Chen and Zheng, Yuanting and Zhou, Yiming and Zumbo, Paul and Tong, Weida and Kreil, David P and Mason, Christopher E and Shi, Leming},
  issn         = {1087-0156},
  journal      = {NATURE BIOTECHNOLOGY},
  keywords     = {GENOME ANNOTATION,GENE-EXPRESSION ANALYSIS,ARRAYS,TRANSCRIPTOME,CALIBRATION,ALIGNER,PROJECT,CELLS,BIAS,PCR},
  language     = {eng},
  number       = {9},
  pages        = {903--914},
  title        = {A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium},
  url          = {http://dx.doi.org/10.1038/nbt.2957},
  volume       = {32},
  year         = {2014},
}

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