{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T14:47:21Z","timestamp":1724424441321},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2003,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: SAGE (Serial Analysis of Gene Expression) can be used to estimate the number of unique transcripts in a transcriptome. A simple estimator that corrects for sequencing and sampling errors was applied to a SAGE library (137\u2009832 tags) obtained from mouse embryonic stem cells, and also to Monte Carlo simulated libraries generated using assumed distributions of\u2018 true\u2019 expression levels consistent with the data.<\/jats:p>\n               <jats:p>Results: When the corrected data themselves were taken as the underlying model of \u2018ground truth\u2019, the estimator converged to the \u2018 true\u2019 value (53\u2009535) only after counting 300\u2009000 simulated tags, more than twice the number in the experiment. The SAGE data could also be well fit by a Monte Carlo model based on a truncated inverse-square distribution of expression levels, with 130\u2009000 \u2018true\u2019 transcripts and 106 samples needed for convergence. We conclude that the size of a transcriptome is ill-determined from SAGE libraries of even moderately large size. In order to obtain a valid estimate, one must sample a number of tags inversely proportional to the lowest abundance level, which is not known a priori. This constrains the design of SAGE experiments intended to determine biological complexity.<\/jats:p>\n               <jats:p>Availability: The \u2018homemade\u2019 software used for this analysis was not designed for general or \u2018production\u2019 use, but the authors will be happy to share Fortran sourcecode with interested parties.<\/jats:p>\n               <jats:p>Contact: sternm@grc.nia.nih.gov<\/jats:p>\n               <jats:p>* To whom correspondence should be addressed.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btg018","type":"journal-article","created":{"date-parts":[[2003,2,28]],"date-time":"2003-02-28T19:57:40Z","timestamp":1046462260000},"page":"443-448","source":"Crossref","is-referenced-by-count":22,"title":["Can transcriptome size be estimated from SAGE catalogs?"],"prefix":"10.1093","volume":"19","author":[{"given":"Michael D.","family":"Stern","sequence":"first","affiliation":[{"name":"Laboratory of Cardiovascular Science, Gerontology Research Center, National Institute on Aging, NIH, 5600 Nathan Shock Drive, Baltimore, MD 21224, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sergey V.","family":"Anisimov","sequence":"additional","affiliation":[{"name":"Laboratory of Cardiovascular Science, Gerontology Research Center, National Institute on Aging, NIH, 5600 Nathan Shock Drive, Baltimore, MD 21224, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kenneth R.","family":"Boheler","sequence":"additional","affiliation":[{"name":"Laboratory of Cardiovascular Science, Gerontology Research Center, National Institute on Aging, NIH, 5600 Nathan Shock Drive, Baltimore, MD 21224, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2003,3,1]]},"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/19\/4\/443\/48903978\/bioinformatics_19_4_443.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/19\/4\/443\/48903978\/bioinformatics_19_4_443.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T16:44:31Z","timestamp":1674665071000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/19\/4\/443\/218693"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,3,1]]},"references-count":0,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2003,3,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btg018","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2003,3,1]]},"published":{"date-parts":[[2003,3,1]]}}}