{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T14:51:23Z","timestamp":1770216683067,"version":"3.49.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2005,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: There are many different gene expression technologies, including cDNA and oligo-based microarrays, SAGE and MPSS. For each organism of interest, coverage of the transcriptome and the genome will be different. We address the question of what level of coverage is required to exploit the sensitivity of the different technologies, and what is the sensitivity of the different approaches in the experimental study.<\/jats:p>\n               <jats:p>Results: We estimate the transcriptome coverage by randomly sampling transcripts from a pre-defined tag-to-gene mapping function. For a given microarray experiment, we locate the thresholds in intensities that define the distribution of transcript abundance. These values are compared against the distribution obtained by applying the same thresholds to the intensities from differentially expressed genes. The ratio of these two distributions meets at the equilibrium defining sensitivity. We conclude that a collection of \u223c340\u2009000 sequences is adequate for microarrays, but not large enough for maximum utilization of tag-based technologies. In the absence of large-scale sequencing, the majority of the tags detected by the latter approaches will remain unidentified until the genome sequence is available.<\/jats:p>\n               <jats:p>Contact: \u00a0Tony.Reverter-Gomez@csiro.au<\/jats:p>","DOI":"10.1093\/bioinformatics\/bth472","type":"journal-article","created":{"date-parts":[[2004,8,13]],"date-time":"2004-08-13T00:15:36Z","timestamp":1092356136000},"page":"80-89","source":"Crossref","is-referenced-by-count":24,"title":["A rapid method for computationally inferring transcriptome coverage and microarray sensitivity"],"prefix":"10.1093","volume":"21","author":[{"given":"A.","family":"Reverter","sequence":"first","affiliation":[{"name":"Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct 306 Carmody Road, St Lucia, QLD 4067, Australia"}]},{"given":"S. M.","family":"McWilliam","sequence":"additional","affiliation":[{"name":"Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct 306 Carmody Road, St Lucia, QLD 4067, Australia"}]},{"given":"W.","family":"Barris","sequence":"additional","affiliation":[{"name":"Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct 306 Carmody Road, St Lucia, QLD 4067, Australia"}]},{"given":"B. P.","family":"Dalrymple","sequence":"additional","affiliation":[{"name":"Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct 306 Carmody Road, St Lucia, QLD 4067, Australia"}]}],"member":"286","published-online":{"date-parts":[[2004,8,12]]},"reference":[{"key":"2023013107193164800_B1","doi-asserted-by":"crossref","unstructured":"Berthier, D., Qu\u00e9r\u00e9, R., Thevenon, S., Belemsaga, E., Piquemal, D., Marti, J., Maillard, J.-C. 2003Serial analysis of gene expression (SAGE) in bovine trypanotolerance: preliminary results. Genet. Sel. Evol.35Suppl. 1,S35","DOI":"10.1186\/1297-9686-35-S1-S35"},{"key":"2023013107193164800_B2","doi-asserted-by":"crossref","unstructured":"Bickel, D.R. 2004Degrees of differential gene expression: detecting biologically significant expression differences and estimating their magnitudes. Bioinformatics20682\u2013688","DOI":"10.1093\/bioinformatics\/btg468"},{"key":"2023013107193164800_B3","doi-asserted-by":"crossref","unstructured":"Brenner, S., Johnson, M., Bridgham, J., Golda, G., Lloyd, D.H., Johnson, D., Luo, S., McCurdy, S., Foy, M., Ewan, M., et al. 2000Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nat. Biotechnol.18630\u2013634","DOI":"10.1038\/76469"},{"key":"2023013107193164800_B4","doi-asserted-by":"crossref","unstructured":"Brown, E.N., McDermott, T.J., Bloch, K.J., McCollom, A.D. 1996Defining the smallest analyte concentration an immunoassay can measure. Clinical Chem.42893\u2013903","DOI":"10.1093\/clinchem\/42.6.893"},{"key":"2023013107193164800_B5","doi-asserted-by":"crossref","unstructured":"Callow, M.J., Dudoit, S., Gong, E.L., Speed, T.P., Rubin, E.M. 2000Microarray expression profiling identifies genes with altered expression in HDL-deficient mice. Genome Res.102022\u20132029","DOI":"10.1101\/gr.147200"},{"key":"2023013107193164800_B6","doi-asserted-by":"crossref","unstructured":"Chudin, E., Walker, R., Kosaka, A., Wu, S.X., Rabert, D., Chang, T.K., Kreder, D.E. 2001Assessment of the relationship between signal intensities and transcript concentration for Affymetrix GeneChip\u00ae arrays. Genome Biol.3research0005.1\u2013research0005.10","DOI":"10.1186\/gb-2001-3-1-research0005"},{"key":"2023013107193164800_B7","unstructured":"Dror, R.O., Murnick, J.G., Rinaldi, N.J., Marinescu, V.D., Rifkin, R.M., Young, R.A. 2003Bayesian estimation of transcript level using a general model of array measurement noise. J. Comput. Biol.10433\u2013452"},{"key":"2023013107193164800_B8","doi-asserted-by":"crossref","unstructured":"Dudley, A.M., Aach, J., Steffen, M.A., Church, G.M. 2002Measuring absolute expression with microarrays with a calibrated reference sample and an extended signal intensity range. Proc. Natl Acad. Sci. USA997554\u20137559","DOI":"10.1073\/pnas.112683499"},{"key":"2023013107193164800_B9","unstructured":"Everitt, B.S. The Cambridge Dictionary of Statistics2002 2nd edn , Cambridge, UK  Cambridge University Press"},{"key":"2023013107193164800_B10","doi-asserted-by":"crossref","unstructured":"Hanley, J.A. and McNeil, B.J. 1982The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology143,  pp. 29\u201336","DOI":"10.1148\/radiology.143.1.7063747"},{"key":"2023013107193164800_B11","doi-asserted-by":"crossref","unstructured":"Hawken, R.J., Barris, W.C., McWilliam, S., Dalrymple, B.P. 2004An Interactive Bovine In silico SNP database (IBISS). Mamm. Genome15819\u2013827","DOI":"10.1007\/s00335-004-2382-4"},{"key":"2023013107193164800_B12","doi-asserted-by":"crossref","unstructured":"Heagerty, P.J., Lumley, T., Pepe, M. 2000Time dependent ROC curves for censored survival data and a diagnostic marker. Biometrics56337\u2013344","DOI":"10.1111\/j.0006-341X.2000.00337.x"},{"key":"2023013107193164800_B13","unstructured":"Hraber, P.T. 2001Discovering molecular mechanisms of mutualism with computational approaches to endosymbiosis.  , Albuquerque, NM, USA  PhD Dissertation University of New Mexico"},{"key":"2023013107193164800_B14","doi-asserted-by":"crossref","unstructured":"Ishii, M., Hashimoto, S., Tsutsumi, S., Wada, Y., Matsushima, K., Kodama, T., Aburatani, H. 2000Direct comparison of GeneChip and SAGE on the quantitative accuracy in transcript profiling analysis. Genomics68136\u2013143","DOI":"10.1006\/geno.2000.6284"},{"key":"2023013107193164800_B15","doi-asserted-by":"crossref","unstructured":"Jongeneel, C.V., Iseli, C., Stevenson, B.J., Riggins, G.J., Lal, A., Mackay, A., Harris, R.A., O'Hare, M.J., Neville, A.M., Simpson, A.J., Strausberg, R.L. 2003Comprehensive sampling of gene expression in human cell lines with massively parallel signature sequencing. Proc. Natl Acad. Sci. USA1004702\u20134705","DOI":"10.1073\/pnas.0831040100"},{"key":"2023013107193164800_B16","doi-asserted-by":"crossref","unstructured":"Kane, M.D., Jatkoe, T.A., Stumpf, C.R., Lu, J., Thomas, J.D., Madore, S.J. 2000Assessment of the sensitivity and specificity of oligonucleotide (50\u2009mer) microarrays. Nucleic Acids Res.284552\u20134557","DOI":"10.1093\/nar\/28.22.4552"},{"key":"2023013107193164800_B17","doi-asserted-by":"crossref","unstructured":"Kuznetsov, V.A. 2001Distribution associated with stochastic processes of gene expression in a single eukaryotic cell EURASIP. J. Appl. Signal Proc.4285\u2013296","DOI":"10.1155\/S1110865701000294"},{"key":"2023013107193164800_B18","unstructured":"Kuznetsov, V.A., Knott, G.D., Bonner, R.F. 2002General statistics of stochastic process of gene expression in eukaryotic cells. Genetics1611321\u20131332"},{"key":"2023013107193164800_B19","doi-asserted-by":"crossref","unstructured":"Lash, A.E., Tolstoshev, C.M., Wagner, L., Schuler, G.D., Strausberg, R.L., Riggins, G.J., Altschul, F. 2000SAGEmap: a public gene expression resource. Genome Res.101051\u20131060","DOI":"10.1101\/gr.10.7.1051"},{"key":"2023013107193164800_B20","doi-asserted-by":"crossref","unstructured":"Lee, H.S., Wang, J., Tian, L., Jiang, H., Black, M.A., Madlung, A., Watson, B., Lukens, L., Pires, J.C., Wang, J.J., et al. 2004Sensitivity of 70-mer oligonucleotides and cDNAs for microarray analysis of gene expression in Arabidopsis and its related species. Plant Biotechnol. J.245\u201352","DOI":"10.1046\/j.1467-7652.2003.00048.x"},{"key":"2023013107193164800_B21","doi-asserted-by":"crossref","unstructured":"Lemon, W.J., Liyanarachchi, S., You, M. 2003A high performance test of differential gene expression for oligonucleotide arrays. Genome Biol.4R67","DOI":"10.1186\/gb-2003-4-10-r67"},{"key":"2023013107193164800_B22","unstructured":"Li, C. and Wong, W.H. 2001Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc. Natl Acad. Sci. USA9831\u201336"},{"key":"2023013107193164800_B23","doi-asserted-by":"crossref","unstructured":"Li, H. and Gui, J. 2004Partial Cox regression analysis for high-dimensional microarray gene expression data. Bioinformatics20Suppl. 1,i208\u2013i215","DOI":"10.1093\/bioinformatics\/bth900"},{"key":"2023013107193164800_B24","doi-asserted-by":"crossref","unstructured":"Lin, J.Y., Pollack, J.R., Chou, F.L., Rees, C.A., Christian, A.T., Bedford, J.S., Brown, P.O., Ginsberg, M.H. 2002Physical mapping of genes in somatic cell radiation hybrids by comparative genomic hybridization to cDNA microarrays. Genome Biol.3research0026.1\u2013research0026.7","DOI":"10.1186\/gb-2002-3-6-research0026"},{"key":"2023013107193164800_B25","unstructured":"Lockhart, D.J. and Winzeler, E.A. 2000Genomics, gene expression, and DNA arrays. Nature405827\u2013836"},{"key":"2023013107193164800_B26","doi-asserted-by":"crossref","unstructured":"Meissner, N., Radke, J., Hedges, J.F., White, M., Behnke, M., Bertolino, S., Mitchell, A., Jutila, M.A. 2003Serial analysis of gene expression in circulating \u03b3\u03b4 T cell subsets defines distinct immunoregulatory phenotypes and unexpected gene expression profiles. J. Immunol.170356\u2013364","DOI":"10.4049\/jimmunol.170.1.356"},{"key":"2023013107193164800_B27","doi-asserted-by":"crossref","unstructured":"Miller, R.T., Christoffels, A.G., Gopalakrishnan, C., Burke, J., Ptitsyn, A.A., Broveak, T.R., Hide, W.A. 1999A comprehensive approach to clustering of expressed human gene sequence: the sequence tag alignment and consensus knowledge base. Genome Res.111143\u201355","DOI":"10.1101\/gr.9.11.1143"},{"key":"2023013107193164800_B28","doi-asserted-by":"crossref","unstructured":"Morris, J.S., Baggerly, K.A., Coombes, K.R. 2003Bayesian shrinkage estimation of the relative abundance of mRNA transcripts using SAGE. Biometrics59476\u2013486","DOI":"10.1111\/1541-0420.00057"},{"key":"2023013107193164800_B29","doi-asserted-by":"crossref","unstructured":"Neill, J.D. and Ridpath, J.F. 2003Gene expression changes in BVDV2-infected MDBK cells. Biologicals3197\u2013102","DOI":"10.1016\/S1045-1056(03)00022-8"},{"key":"2023013107193164800_B30","unstructured":"Nicholson, W. Microeconomic Theory: Basic Principles and Extensions1985 3rd edn , New York  The Dryden Press"},{"key":"2023013107193164800_B31","doi-asserted-by":"crossref","unstructured":"O'Malley, A.J. and Deely, J.J. 2003Bayesian measures of the minimum detectable concentration of an immunoassay. Aust. N. Z. J. Stat.45,  pp. 43\u201365","DOI":"10.1111\/1467-842X.00260"},{"key":"2023013107193164800_B32","doi-asserted-by":"crossref","unstructured":"Pepe, M.S., Longton, G., Anderson, G.L., Schummer, M. 2003Selecting differentially expressed genes from microarray experiments. Biometrics59133\u2013142","DOI":"10.1111\/1541-0420.00016"},{"key":"2023013107193164800_B33","doi-asserted-by":"crossref","unstructured":"Tu, Y., Stolovitzky, G., Klein, U. 2002Quantitative noise analysis for gene expression microarray experiments. Proc. Natl Acad. Sci., USA9914031\u201314036","DOI":"10.1073\/pnas.222164199"},{"key":"2023013107193164800_B34","doi-asserted-by":"crossref","unstructured":"Ueda, H.R., Hayashi, S., Matsuyama, S., Yomo, T., Hashimoto, S., Kay, S.A., Hogenesch, J.B., Lino, M. 2004Universality and flexibility in gene expression from bacteria to human. Proc. Natl Acad. Sci., USA1013765\u20133769","DOI":"10.1073\/pnas.0306244101"},{"key":"2023013107193164800_B35","unstructured":"Velculescu, V.E., Zhang, L., Vogelstein, B., Kinzler, K.W. 1995Serial analysis of gene expression. Science270484\u2013487"},{"key":"2023013107193164800_B36","doi-asserted-by":"crossref","unstructured":"Velculescu, V.E., Zhang, L., Zhou, W., Vogelstein, J., Basrai, M.A., Bassett, E.E., Hieter, P., Vogelstein, B., Kinzler, K.W. 1997Characterization of the yeast transcriptome. Cell88243\u2013251","DOI":"10.1016\/S0092-8674(00)81845-0"},{"key":"2023013107193164800_B37","doi-asserted-by":"crossref","unstructured":"Wang, H., Hubbell, E., Hu, J., Mei, G., Cline, M., Lu, G., Clark, T., Siani-Rose, M.A., Ares, M., Kulp, D.C., Haussler, D. 2003Gene structure-based splice variant deconvolution using a microarray platform. Bioinformatics19Supp1. 1,i315\u2013i322","DOI":"10.1093\/bioinformatics\/btg1044"},{"key":"2023013107193164800_B38","doi-asserted-by":"crossref","unstructured":"Zien, A., Fluck, J., Zimmer, R., Lengauer, T. 2003Microarrays: how many do you need?. J. Comput. Biol.10653\u2013667","DOI":"10.1145\/565196.565239"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/21\/1\/80\/48961897\/bioinformatics_21_1_80.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/21\/1\/80\/48961897\/bioinformatics_21_1_80.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T09:56:45Z","timestamp":1675159005000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/21\/1\/80\/212643"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004,8,12]]},"references-count":38,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2005,1,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bth472","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2005,1,1]]},"published":{"date-parts":[[2004,8,12]]}}}