References[1] United states patent application 0090093378: Method for sequencing a polynucleotide template.[2] Albert E. Ayoub, Sunghee Oh, Yanhua Xie, Jing Leng, Justin Cotney, Martin H. Dominguez, James P. Noonan, and Pasko Rakic. Transcriptional programs in transient embryonic zones of the cerebral cortex defined by high-resolution mRNA sequencing. Proceedings of the National Academy of Sciences, 108(36):1495014955, September 2011.[3] Courtney C. Babbitt, Olivier Fedrigo, Adam D. Pfefferle, Alan P. Boyle, Julie E. Horvath, Terrence S. Furey, and Gregory A. Wray. Both noncoding and Protein-Coding RNAs contribute to gene expression evolution in the primate brain. Genome Biology and Evolution, 2(0):6779, January 2010.[4] Andrew H. Beck, Ziming Weng, Daniela M. Witten, Shirley Zhu, Joseph W. Foley, Phil Lacroute, Cheryl L. Smith, Robert Tibshirani, Matt van de Rijn, Arend Sidow, and Robert B. West. 3'-end sequencing for expression quantification (3SEQ) from archival tumor samples. PloS one, 5(1):e8768+, January 2010.[5] Regina Bohnert, Jonas Behr, and Gunnar Ratsch. Transcript quantification with RNA-seq data. BMC Bioinformatics, 10(Suppl 13):P5+, October 2009.[6] James Bullard, Elizabeth Purdom, Kasper Hansen, and Sandrine Dudoit. Evaluation of statistical methods for normalization and differential expression in mRNA-seq experiments. BMC Bioinformatics, 11(1):94+, February 2010.[7] Nicole Cloonan, Alistair R. R. Forrest, Gabriel Kolle, Brooke B. A. Gardiner, Geoffrey J. Faulkner, Mellissa K. Brown, Darrin F. Taylor, Anita L. Steptoe, Shivangi Wani, Graeme Bethel, Alan J. Robertson, Andrew C. Perkins, Stephen J. Bruce, Clarence C. Lee, Swati S. Ranade, Heather E. Peckham, Jonathan M. Manning, Kevin J. McKernan, and Sean M. Grimmond. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nature Methods, 5(7):613619, May 2008.[8] Marie-Agnes A. Dillies, Andrea Rau, Julie Aubert, Christelle Hennequet-Antier, Marine Jeanmougin, Nicolas Servant, Celine Keime, Guillemette Marot, David Castel, Jordi Estelle, Gregory Guernec, Bernd Jagla, Luc Jouneau, Denis Laloe, Caroline Le Gall, Brigitte Schaeffer, Stephane Le Crom, Mickael Guedj, Florence Jaffrezic, and French StatOmique Consortium. A comprehensive evaluation of normalization methods for illumina high-throughput RNA sequencing data analysis. Briefings in bioinformatics, 14(6):671683, November 2013. [9] Simone A. Fietz, Robert Lachmann, Holger Brandl, Martin Kircher, Nikolay Samusik, Roland Schroder, Naharajan Lakshmanaperumal, Ian Henry, Johannes Vogt, Axel Riehn, Wolfgang Distler, Robert Nitsch, Wolfgang Enard, Svante Paabo, and Wieland B. Huttner. Transcriptomes of germinal zones of human and mouse fetal neocortex suggest a role of extracellular matrix in progenitor self-renewal. Proceedings of the National Academy of Sciences of the United States of America, 109(29):1183611841, July 2012.[10] Xing Fu, Ning Fu, Song Guo, Zheng Yan, Ying Xu, Hao Hu, Corinna Menzel, Wei Chen, Yixue Li, Rong Zeng, and Philipp Khaitovich. Estimating accuracy of RNA-seq and microarrays with proteomics. BMC Genomics, 10(1):161+, April 2009.[11] Yoav Gilad, Jonathan K. Pritchard, and Kevin Thornton. Characterizing natural variation using next-generation sequencing technologies. Trends in Genetics, 25(10):463471, October 2009.[12] Shin-ichi Hashimoto, Wei Qu, Budrul Ahsan, Katsumi Ogoshi, Atsushi Sasaki, Yoichiro Nakatani, Yongjun Lee, Masako Ogawa, Akio Ametani, Yutaka Suzuki, Sumio Sugano, Clarence C. Lee, Robert C. Nutter, Shinichi Morishita, and Kouji Matsushima. High-Resolution analysis of the 5-End transcriptome using a next generation DNA sequencer. PLoS ONE, 4(1):e4108+, January 2009.[13] David Hiller, Hui Jiang, Weihong Xu, and Wing Hung H. Wong. Identifiability of isoform deconvolution from junction arrays and RNA-seq. Bioinformatics (Oxford, England), 25(23):30563059, December 2009.[14] Nicholas T. Ingolia, Sina Ghaemmaghami, John R. Newman, and Jonathan S. Weissman. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science (New York, N.Y.), 324(5924):218223, April 2009.[15] Hui Jiang and Wing H. Wong. Statistical inferences for isoform expression in RNA-seq. Bioinformatics, 25(8):10261032, April 2009.[16] Amit N. Khachane and Paul M. Harrison. Mining mammalian transcript data for functional long non-coding RNAs. PloS one, 5(4):e10316+, April 2010.[17] Joshua Levin, Michael Berger, Xian Adiconis, Peter Rogov, Alexandre Melnikov, Timothy Fennell, Chad Nusbaum, Levi Garraway, and Andreas Gnirke. Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts. Genome Biology, 10(10):R115+, October 2009.[18] Bo Li, Victor Ruotti, Ron M. Stewart, James A. Thomson, and Colin N. Dewey. RNA-seq gene expression estimation with read mapping uncertainty. Bioinformatics (Oxford, England), 26(4):493500, February 2010.[19] Hairi Li, Michael T. Lovci, Young-Soo S. Kwon, Michael G. Rosenfeld, Xiang-Dong D. Fu, and Gene W. Yeo. Determination of tag density required for digital transcriptome analysis: application to an androgen-sensitive prostate cancer model. Proceedings of the National Academy of Sciences of the United States of America, 105(51):2017920184, December 2008.[20] John C. Marioni, Christopher E. Mason, Shrikant M. Mane, Matthew Stephens, and Yoav Gilad. RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome research, 18(9):15091517, September 2008.[21] Ali Mortazavi, Brian A. Williams, Kenneth McCue, Lorian Schaeffer, and Barbara Wold. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat Meth, 5(7):621628, July 2008.[22] Alicia Oshlack and Matthew J. Wakefield. Transcript length bias in RNA-seq data confounds systems biology. Biology Direct, 4(1):1410, December 2009.[23] Zhengqing Ouyang, Qing Zhou, and Wing H. Wong. ChIP-seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells. Proceedings of the National Academy of Sciences, 106(51):2152121526, December 2009.[24] Fatih Ozsolak, Alon Goren, Melissa Gymrek, Mitchell Guttman, Aviv Regev, Bradley E. Bernstein, and Patrice M. Milos. Digital transcriptome profiling from attomole-level RNA samples. Genome Research, 20(4):519525, April 2010.[25] Fatih Ozsolak, Adam R. Platt, Dan R. Jones, Jeffrey G. Reifenberger, Lauryn E. Sass, Peter McInerney, John F. Thompson, Jayson Bowers, Mirna Jarosz, and Patrice M. Milos. Direct RNA sequencing. Nature, 461(7265):814818, September 2009.[26] Shirley Pepke, Barbara Wold, and Ali Mortazavi. Computation for ChIP-seq and RNA-seq studies. Nat Meth, 6(11s):S22S32, November 2009.[27] Daniel Ramskold, Eric T. Wang, Christopher B. Burge, and Rickard Sandberg. An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS Comput Biol, 5(12):e1000598+, December 2009.[28] Mark D. Robinson and Alicia Oshlack. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biology, 11(3):R25+, March 2010.[29] T. Svingen, C. M. Spiller, K. Kashimada, V. R. Harley, and P. Koopman. Identification of suitable normalizing genes for quantitative real-time RT-PCR analysis of gene expression in fetal mouse gonads. Sexual development : genetics, molecular biology, evolution, endocrinology, embryology, and pathology of sex determination and differentiation, 3(4):194204, 2009.[30] Cole Trapnell, Lior Pachter, and Steven L. Salzberg. TopHat: discovering splice junctions with RNA-seq. Bioinformatics, 25(9):11051111, May 2009.[31] Gunter P. Wagner, Koryu Kin, and Vincent J. Lynch. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory in biosciences = Theorie in den Biowissenschaften, 131(4):281285, December 2012.[32] Eric T. Wang, Rickard Sandberg, Shujun Luo, Irina Khrebtukova, Lu Zhang, Christine Mayr, Stephen F. Kingsmore, Gary P. Schroth, and Christopher B. Burge. Alternative isoform regulation in human tissue transcriptomes. Nature, 456(7221):470476, November 2008.[33] Likun Wang, Zhixing Feng, Xi Wang, Xiaowo Wang, and Xuegong Zhang. DEGseq: an r package for identifying differentially expressed genes from RNA-seq data. Bioinformatics, 26(1):136138, January 2010.[34] Zhong Wang, Mark Gerstein, and Michael Snyder. RNA-seq: a revolutionary tool for transcriptomics. Nature reviews. Genetics, 10(1):5763, January 2009.[35] Brian T. Wilhelm and Josette-Renee Landry. RNA-seqquantitative measurement of expression through massively parallel RNA-sequencing. Methods, 48(3):249257, July 2009.