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References, ???? United states patent application 0090093378: Method for sequencing a polynucleotide template. URL http://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&u=%2Fnetahtml%2FPTO%2Fsearch-adv.html&r=2&p=1&f=G&l=50&d=PG01&S1=20070128624&OS=20070128624&RS=20070128624Ayoub, A. E., Oh, S., Xie, Y., Leng, J., Cotney, J., Dominguez, M. H., Noonan, J. P., Rakic, P., Sep. 2011. 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. URL http://dx.doi.org/10.1073/pnas.1112213108Babbitt, C. C., Fedrigo, O., Pfefferle, A. D., Boyle, A. P., Horvath, J. E., Furey, T. S., Wray, G. A., Jan. 2010. Both noncoding and Protein-Coding RNAs contribute to gene expression evolution in the primate brain. Genome Biology and Evolution 2 (0), 6779. URL http://dx.doi.org/10.1093/gbe/evq002Beck, A. H., Weng, Z., Witten, D. M., Zhu, S., Foley, J. W., Lacroute, P., Smith, C. L., Tibshirani, R., van de Rijn, M., Sidow, A., West, R. B., Jan. 2010. 3'-end sequencing for expression quantification (3SEQ) from archival tumor samples. PloS one 5 (1), e8768+. URL http://dx.doi.org/10.1371/journal.pone.0008768Bohnert, R., Behr, J., Ratsch, G., Oct. 2009. Transcript quantification with RNA-seq data. BMC Bioinformatics 10 (Suppl 13), P5+. URL http://dx.doi.org/10.1186/1471-2105-10-s13-p5Bullard, J., Purdom, E., Hansen, K., Dudoit, S., Feb. 2010. Evaluation of statistical methods for normalization and differential expression in mRNA-seq experiments. BMC Bioinformatics 11 (1), 94+. URL http://dx.doi.org/10.1186/1471-2105-11-94Cloonan, N., Forrest, A. R. R., Kolle, G., Gardiner, B. B. A., Faulkner, G. J., Brown, M. K., Taylor, D. F., Steptoe, A. L., Wani, S., Bethel, G., Robertson, A. J., Perkins, A. C., Bruce, S. J., Lee, C. C., Ranade, S. S., Peckham, H. E., Manning, J. M., McKernan, K. J., Grimmond, S. M., May 2008. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nature Methods 5 (7), 613619. URL http://dx.doi.org/10.1038/nmeth.1223Dillies, M.-A. A., Rau, A., Aubert, J., Hennequet-Antier, C., Jeanmougin, M., Servant, N., Keime, C., Marot, G., Castel, D., Estelle, J., Guernec, G., Jagla, B., Jouneau, L., Laloe, D., Le Gall, C., Schaeffer, B., Le Crom, S., Guedj, M., Jaffrezic, F., French StatOmique Consortium, Nov. 2013. A comprehensive evaluation of normalization methods for illumina high-throughput RNA sequencing data analysis. Briefings in bioinformatics 14 (6), 671683. URL http://dx.doi.org/10.1093/bib/bbs046Fietz, S. A., Lachmann, R., Brandl, H., Kircher, M., Samusik, N., Schroder, R., Lakshmanaperumal, N., Henry, I., Vogt, J., Riehn, A., Distler, W., Nitsch, R., Enard, W., Paabo, S., Huttner, W. B., Jul. 2012. 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. URL http://dx.doi.org/10.1073/pnas.1209647109Fu, X., Fu, N., Guo, S., Yan, Z., Xu, Y., Hu, H., Menzel, C., Chen, W., Li, Y., Zeng, R., Khaitovich, P., Apr. 2009. Estimating accuracy of RNA-seq and microarrays with proteomics. BMC Genomics 10 (1), 161+. URL http://dx.doi.org/10.1186/1471-2164-10-161Gilad, Y., Pritchard, J. K., Thornton, K., Oct. 2009. Characterizing natural variation using next-generation sequencing technologies. Trends in Genetics 25 (10), 463471. URL http://dx.doi.org/10.1016/j.tig.2009.09.003Hashimoto, S.-i., Qu, W., Ahsan, B., Ogoshi, K., Sasaki, A., Nakatani, Y., Lee, Y., Ogawa, M., Ametani, A., Suzuki, Y., Sugano, S., Lee, C. C., Nutter, R. C., Morishita, S., Matsushima, K., Jan. 2009. High-Resolution analysis of the 5-End transcriptome using a next generation DNA sequencer. PLoS ONE 4 (1), e4108+. URL http://dx.doi.org/10.1371/journal.pone.0004108Hiller, D., Jiang, H., Xu, W., Wong, W. H. H., Dec. 2009. Identifiability of isoform deconvolution from junction arrays and RNA-seq. Bioinformatics (Oxford, England) 25 (23), 30563059. URL http://dx.doi.org/10.1093/bioinformatics/btp544Ingolia, N. T., Ghaemmaghami, S., Newman, J. R., Weissman, J. S., Apr. 2009. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science (New York, N.Y.) 324 (5924), 218223. URL http://dx.doi.org/10.1126/science.1168978Jiang, H., Wong, W. H., Apr. 2009. Statistical inferences for isoform expression in RNA-seq. Bioinformatics 25 (8), 10261032. URL http://dx.doi.org/10.1093/bioinformatics/btp113Khachane, A. N., Harrison, P. M., Apr. 2010. Mining mammalian transcript data for functional long non-coding RNAs. PloS one 5 (4), e10316+. URL http://dx.doi.org/10.1371/journal.pone.0010316Levin, J., Berger, M., Adiconis, X., Rogov, P., Melnikov, A., Fennell, T., Nusbaum, C., Garraway, L., Gnirke, A., Oct. 2009. Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts. Genome Biology 10 (10), R115+. URL http://dx.doi.org/10.1186/gb-2009-10-10-r115Li, B., Ruotti, V., Stewart, R. M., Thomson, J. A., Dewey, C. N., Feb. 2010. RNA-seq gene expression estimation with read mapping uncertainty. Bioinformatics (Oxford, England) 26 (4), 493500. URL http://dx.doi.org/10.1093/bioinformatics/btp692Li, H., Lovci, M. T., Kwon, Y.-S. S., Rosenfeld, M. G., Fu, X.-D. D., Yeo, G. W., Dec. 2008. 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. URL http://dx.doi.org/10.1073/pnas.0807121105Marioni, J. C., Mason, C. E., Mane, S. M., Stephens, M., Gilad, Y., Sep. 2008. RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome research 18 (9), 15091517. URL http://dx.doi.org/10.1101/gr.079558.108Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., Wold, B., Jul. 2008. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat Meth 5 (7), 621628. URL http://dx.doi.org/10.1038/nmeth.1226Oshlack, A., Wakefield, M. J., Dec. 2009. Transcript length bias in RNA-seq data confounds systems biology. Biology Direct 4 (1), 1410. URL http://dx.doi.org/10.1186/1745-6150-4-14Ouyang, Z., Zhou, Q., Wong, W. H., Dec. 2009. 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. URL http://dx.doi.org/10.1073/pnas.0904863106Ozsolak, F., Goren, A., Gymrek, M., Guttman, M., Regev, A., Bernstein, B. E., Milos, P. M., Apr. 2010. Digital transcriptome profiling from attomole-level RNA samples. Genome Research 20 (4), 519525. URL http://dx.doi.org/10.1101/gr.102129.109Ozsolak, F., Platt, A. R., Jones, D. R., Reifenberger, J. G., Sass, L. E., McInerney, P., Thompson, J. F., Bowers, J., Jarosz, M., Milos, P. M., Sep. 2009. Direct RNA sequencing. Nature 461 (7265), 814818. URL http://dx.doi.org/10.1038/nature08390Pepke, S., Wold, B., Mortazavi, A., Nov. 2009. Computation for ChIP-seq and RNA-seq studies. Nat Meth 6 (11s), S22S32. URL http://dx.doi.org/10.1038/nmeth.1371Ramskold, D., Wang, E. T., Burge, C. B., Sandberg, R., Dec. 2009. An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS Comput Biol 5 (12), e1000598+. URL http://dx.doi.org/10.1371/journal.pcbi.1000598Robinson, M. D., Oshlack, A., Mar. 2010. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biology 11 (3), R25+. URL http://dx.doi.org/10.1186/gb-2010-11-3-r25Svingen, T., Spiller, C. M., Kashimada, K., Harley, V. R., Koopman, P., 2009. 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. URL http://dx.doi.org/10.1159/000228720Trapnell, C., Pachter, L., Salzberg, S. L., May 2009. TopHat: discovering splice junctions with RNA-seq. Bioinformatics 25 (9), 11051111. URL http://dx.doi.org/10.1093/bioinformatics/btp120Wagner, G. P., Kin, K., Lynch, V. J., Dec. 2012. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory in biosciences = Theorie in den Biowissenschaften 131 (4), 281285. URL http://dx.doi.org/10.1007/s12064-012-0162-3Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., Burge, C. B., Nov. 2008. Alternative isoform regulation in human tissue transcriptomes. Nature 456 (7221), 470476. URL http://dx.doi.org/10.1038/nature07509Wang, L., Feng, Z., Wang, X., Wang, X., Zhang, X., Jan. 2010. DEGseq: an r package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 26 (1), 136138. URL http://dx.doi.org/10.1093/bioinformatics/btp612Wang, Z., Gerstein, M., Snyder, M., Jan. 2009. RNA-seq: a revolutionary tool for transcriptomics. Nature reviews. Genetics 10 (1), 5763. URL http://dx.doi.org/10.1038/nrg2484Wilhelm, B. T., Landry, J.-R., Jul. 2009. RNA-seqquantitative measurement of expression through massively parallel RNA-sequencing. Methods 48 (3), 249257. URL http://dx.doi.org/10.1016/j.ymeth.2009.03.016