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  • Genome Project Standards in...
    Chain, P. S. G.; Grafham, D. V.; Fulton, R. S.; FitzGerald, M. G.; Hostetler, J.; Muzny, D.; Ali, J.; Birren, B.; Bruce, D. C.; Buhay, C.; Cole, J. R.; Ding, Y.; Dugan, S.; Field, D.; Garrity, G. M.; Gibbs, R.; Graves, T.; Han, C. S.; Harrison, S. H.; Highlander, S.; Hugenholtz, P.; Khouri, H. M.; Kodira, C. D.; Kolker, E.; Kyrpides, N. C.; Lang, D.; Lapidus, A.; Malfatti, S. A.; Markowitz, V.; Metha, T.; Nelson, K. E.; Parkhill, J.; Pitluck, S.; Qin, X.; Read, T. D.; Schmutz, J.; Sozhamannan, S.; Sterk, P.; Strausberg, R. L.; Sutton, G.; Thomson, N. R.; Tiedje, J. M.; Weinstock, G.; Wollam, A.; Detter, J. C.

    Science (American Association for the Advancement of Science), 10/2009, Letnik: 326, Številka: 5950
    Journal Article

    More detailed sequence standards that keep up with revolutionary sequencing technologies will aid the research community in evaluating data. For over a decade, genome sequences have adhered to only two standards that are relied on for purposes of sequence analysis by interested third parties ( 1 , 2 ). However, ongoing developments in revolutionary sequencing technologies have resulted in a redefinition of traditional whole-genome sequencing that requires reevaluation of such standards. With commercially available 454 pyrosequencing (followed by Illumina, SOLiD, and now Helicos), there has been an explosion of genomes sequenced under the moniker “draft”; however, these can be very poor quality genomes (due to inherent errors in the sequencing technologies, and the inability of assembly programs to fully address these errors). Further, one can only infer that such draft genomes may be of poor quality by navigating through the databases to find the number and type of reads deposited in sequence trace repositories (and not all genomes have this available), or to identify the number of contigs or genome fragments deposited to the database. The difficulty in assessing the quality of such deposited genomes has created some havoc for genome analysis pipelines and has contributed to many wasted hours. Exponential leaps in raw sequencing capability and greatly reduced prices have further skewed the time- and cost-ratios of draft data generation versus the painstaking process of improving and finishing a genome. The result is an ever-widening gap between drafted and finished genomes that only promises to continue (see the figure, page 236); hence, there is an urgent need to distinguish good from poor data sets.