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10.1186/s12864-017-3771-x http://scihub22266oqcxt.onion/10.1186/s12864-017-3771-x C5437544!5437544 !28521726     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28521726 &cmd=llinks): Failed to open stream: HTTP request failed! 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OrthoFiller: utilising data from multiple species to improve the completeness of genome annotations |pdf=|usr=}}{{28521726 }} gab.com Text OrthoFiller: utilising data from multiple species to improve the completeness of genome annotations JO: BMC Genomics http://www.kidney.de/pget.php?&tw=1&pmid=28521726 #FOAvip BACKROUND: Complete and accurate annotation of sequenced genomes is of paramount importance to their utility and analysis. Differences in gene prediction pipelines mean that genome annotations for a species can differ considerably in the quality and quantity of their predicted genes. Furthermore, genes that are present in genome sequences sometimes fail to be detected by computational gene prediction methods. Erroneously unannotated genes can lead to oversights and inaccurate assertions in biological investigations, especially for smaller-scale genome projects, which rely heavily on computational prediction. RESULTS: Here we present OrthoFiller, a tool designed to address the problem of finding and adding such missing genes to genome annotations. OrthoFiller leverages information from multiple related species to identify those genes whose existence can be verified through comparison with known gene families, but which have not been predicted. By simulating missing gene annotations in real sequence datasets from both plants and fungi we demonstrate the accuracy and utility of OrthoFiller for finding missing genes and improving genome annotations. Furthermore, we show that applying OrthoFiller to existing "complete" genome annotations can identify and correct substantial numbers of erroneously missing genes in these two sets of species. CONCLUSIONS: We show that significant improvements in the completeness of genome annotations can be made by leveraging information from multiple species. Twit Text FOAVip OrthoFiller: utilising data from multiple species to improve the completeness of genome annotations ????BMC Genomics http://www.kidney.de/pget.php?&tw=1&pmid=28521726 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28521726 #FOAvip English Wikipedia <ref>{{Cite pmid|28521726 }}</ref> OrthoFiller: utilising data from multiple species to improve the completeness of genome annotations #MMPMID28521726 Dunne MP ; Kelly S BMC Genomics 2017[May]; 18 (1 ): 390 PMID28521726 show ga BACKROUND: Complete and accurate annotation of sequenced genomes is of paramount importance to their utility and analysis. Differences in gene prediction pipelines mean that genome annotations for a species can differ considerably in the quality and quantity of their predicted genes. Furthermore, genes that are present in genome sequences sometimes fail to be detected by computational gene prediction methods. Erroneously unannotated genes can lead to oversights and inaccurate assertions in biological investigations, especially for smaller-scale genome projects, which rely heavily on computational prediction. RESULTS: Here we present OrthoFiller, a tool designed to address the problem of finding and adding such missing genes to genome annotations. OrthoFiller leverages information from multiple related species to identify those genes whose existence can be verified through comparison with known gene families, but which have not been predicted. By simulating missing gene annotations in real sequence datasets from both plants and fungi we demonstrate the accuracy and utility of OrthoFiller for finding missing genes and improving genome annotations. Furthermore, we show that applying OrthoFiller to existing "complete" genome annotations can identify and correct substantial numbers of erroneously missing genes in these two sets of species. CONCLUSIONS: We show that significant improvements in the completeness of genome annotations can be made by leveraging information from multiple species. |*Databases, Genetic [MESH] |Arabidopsis/genetics [MESH] |Genomics/*methods [MESH] |Molecular Sequence Annotation/*methods [MESH]OrthoFiller: utilising data from multiple species to improve the compl(epmc).pdf DeepDyve Pubget Overpricing