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LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons
Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable ele...
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Published in: | BMC bioinformatics 2008-01, Vol.9 (1), p.18-18, Article 18 |
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description | Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable elements. Therefore, there is a considerable demand for computational identification of transposable elements. LTR retrotransposons, an important subclass of transposable elements, are well suited for computational identification, as they contain long terminal repeats (LTRs).
We have developed a software tool LTRharvest for the de novo detection of full length LTR retrotransposons in large sequence sets. LTRharvest efficiently delivers high quality annotations based on known LTR transposon features like length, distance, and sequence motifs. A quality validation of LTRharvest against a gold standard annotation for Saccharomyces cerevisae and Drosophila melanogaster shows a sensitivity of up to 90% and 97% and specificity of 100% and 72%, respectively. This is comparable or slightly better than annotations for previous software tools. The main advantage of LTRharvest over previous tools is (a) its ability to efficiently handle large datasets from finished or unfinished genome projects, (b) its flexibility in incorporating known sequence features into the prediction, and (c) its availability as an open source software.
LTRharvest is an efficient software tool delivering high quality annotation of LTR retrotransposons. It can, for example, process the largest human chromosome in approx. 8 minutes on a Linux PC with 4 GB of memory. Its flexibility and small space and run-time requirements makes LTRharvest a very competitive candidate for future LTR retrotransposon annotation projects. Moreover, the structured design and implementation and the availability as open source provides an excellent base for incorporating novel concepts to further improve prediction of LTR retrotransposons. |
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We have developed a software tool LTRharvest for the de novo detection of full length LTR retrotransposons in large sequence sets. LTRharvest efficiently delivers high quality annotations based on known LTR transposon features like length, distance, and sequence motifs. A quality validation of LTRharvest against a gold standard annotation for Saccharomyces cerevisae and Drosophila melanogaster shows a sensitivity of up to 90% and 97% and specificity of 100% and 72%, respectively. This is comparable or slightly better than annotations for previous software tools. The main advantage of LTRharvest over previous tools is (a) its ability to efficiently handle large datasets from finished or unfinished genome projects, (b) its flexibility in incorporating known sequence features into the prediction, and (c) its availability as an open source software.
LTRharvest is an efficient software tool delivering high quality annotation of LTR retrotransposons. It can, for example, process the largest human chromosome in approx. 8 minutes on a Linux PC with 4 GB of memory. Its flexibility and small space and run-time requirements makes LTRharvest a very competitive candidate for future LTR retrotransposon annotation projects. Moreover, the structured design and implementation and the availability as open source provides an excellent base for incorporating novel concepts to further improve prediction of LTR retrotransposons.</description><identifier>ISSN: 1471-2105</identifier><identifier>EISSN: 1471-2105</identifier><identifier>DOI: 10.1186/1471-2105-9-18</identifier><identifier>PMID: 18194517</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Algorithms ; Base Sequence ; Chromosome Mapping - methods ; Drosophila melanogaster ; Identification and classification ; Molecular Sequence Data ; Programming Languages ; Retroelements - genetics ; Retrotransposons ; Saccharomyces ; Sequence Alignment - methods ; Sequence Analysis, DNA - methods ; Software</subject><ispartof>BMC bioinformatics, 2008-01, Vol.9 (1), p.18-18, Article 18</ispartof><rights>COPYRIGHT 2008 BioMed Central Ltd.</rights><rights>Copyright © 2008 Ellinghaus et al; licensee BioMed Central Ltd. 2008 Ellinghaus et al; licensee BioMed Central Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b710t-15e342cf26c64b189755676fc1567c2759766fcf8d158e77e944f9ded9912f583</citedby><cites>FETCH-LOGICAL-b710t-15e342cf26c64b189755676fc1567c2759766fcf8d158e77e944f9ded9912f583</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2253517/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2253517/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18194517$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ellinghaus, David</creatorcontrib><creatorcontrib>Kurtz, Stefan</creatorcontrib><creatorcontrib>Willhoeft, Ute</creatorcontrib><title>LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons</title><title>BMC bioinformatics</title><addtitle>BMC Bioinformatics</addtitle><description>Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable elements. Therefore, there is a considerable demand for computational identification of transposable elements. LTR retrotransposons, an important subclass of transposable elements, are well suited for computational identification, as they contain long terminal repeats (LTRs).
We have developed a software tool LTRharvest for the de novo detection of full length LTR retrotransposons in large sequence sets. LTRharvest efficiently delivers high quality annotations based on known LTR transposon features like length, distance, and sequence motifs. A quality validation of LTRharvest against a gold standard annotation for Saccharomyces cerevisae and Drosophila melanogaster shows a sensitivity of up to 90% and 97% and specificity of 100% and 72%, respectively. This is comparable or slightly better than annotations for previous software tools. The main advantage of LTRharvest over previous tools is (a) its ability to efficiently handle large datasets from finished or unfinished genome projects, (b) its flexibility in incorporating known sequence features into the prediction, and (c) its availability as an open source software.
LTRharvest is an efficient software tool delivering high quality annotation of LTR retrotransposons. It can, for example, process the largest human chromosome in approx. 8 minutes on a Linux PC with 4 GB of memory. Its flexibility and small space and run-time requirements makes LTRharvest a very competitive candidate for future LTR retrotransposon annotation projects. Moreover, the structured design and implementation and the availability as open source provides an excellent base for incorporating novel concepts to further improve prediction of LTR retrotransposons.</description><subject>Algorithms</subject><subject>Base Sequence</subject><subject>Chromosome Mapping - methods</subject><subject>Drosophila melanogaster</subject><subject>Identification and classification</subject><subject>Molecular Sequence Data</subject><subject>Programming Languages</subject><subject>Retroelements - genetics</subject><subject>Retrotransposons</subject><subject>Saccharomyces</subject><subject>Sequence Alignment - methods</subject><subject>Sequence Analysis, DNA - methods</subject><subject>Software</subject><issn>1471-2105</issn><issn>1471-2105</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNqFkuFr1DAYxosobk6_-lEKgjCwM0mTJvkiHGPqwYEw5zchpOmbW0bbnEnunP-9qXfMFSfSD2_z5skvyfOkKF5idIaxaN5hynFFMGKVrLB4VBzfNR7f-z8qnsV4gxDmArGnxREWWFKG-XHxbXV1ea3DDmJ6W-qxBGudcTCmPOhK28Ota3soo7fphw5QWh_KDsrR73yuCUxyfiy9LTOnDJCCT0GPceOjH-Pz4onVfYQXh3pSfP1wcXX-qVp9_rg8X6yqlmOUKsygpsRY0piGtlhIzljDG2twLoZwJnmTR1Z0mAngHCSlVnbQSYmJZaI-KZZ7buf1jdoEN-jwU3nt1O-GD2ulQ3KmByWNQEg0xHBpKatlawkTjW4IhTpvITPr_Z612bYDdCZbEXQ_g85nRnet1n6nCGF1tjQDFntA6_w_APMZ4wc1JaWmpJRUeLrQm8Mhgv--zdmowUUDfa9H8NuoOKoJbQT9r5CgmkrJWBa-3gvXOrvgRjvlZCaxWmDOSDYF1Vl19oAqfx0MzvgRrMv92YLT2YKsSXCb1nobo1p-uXwQboKPMYC98wQjNT3mv114dT-KP_LD661_AVMw7Rk</recordid><startdate>20080114</startdate><enddate>20080114</enddate><creator>Ellinghaus, David</creator><creator>Kurtz, Stefan</creator><creator>Willhoeft, Ute</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>7QO</scope><scope>7SS</scope><scope>8FD</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20080114</creationdate><title>LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons</title><author>Ellinghaus, David ; Kurtz, Stefan ; Willhoeft, Ute</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b710t-15e342cf26c64b189755676fc1567c2759766fcf8d158e77e944f9ded9912f583</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Algorithms</topic><topic>Base Sequence</topic><topic>Chromosome Mapping - methods</topic><topic>Drosophila melanogaster</topic><topic>Identification and classification</topic><topic>Molecular Sequence Data</topic><topic>Programming Languages</topic><topic>Retroelements - genetics</topic><topic>Retrotransposons</topic><topic>Saccharomyces</topic><topic>Sequence Alignment - methods</topic><topic>Sequence Analysis, DNA - methods</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ellinghaus, David</creatorcontrib><creatorcontrib>Kurtz, Stefan</creatorcontrib><creatorcontrib>Willhoeft, Ute</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>Biotechnology Research Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ellinghaus, David</au><au>Kurtz, Stefan</au><au>Willhoeft, Ute</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons</atitle><jtitle>BMC bioinformatics</jtitle><addtitle>BMC Bioinformatics</addtitle><date>2008-01-14</date><risdate>2008</risdate><volume>9</volume><issue>1</issue><spage>18</spage><epage>18</epage><pages>18-18</pages><artnum>18</artnum><issn>1471-2105</issn><eissn>1471-2105</eissn><abstract>Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable elements. Therefore, there is a considerable demand for computational identification of transposable elements. LTR retrotransposons, an important subclass of transposable elements, are well suited for computational identification, as they contain long terminal repeats (LTRs).
We have developed a software tool LTRharvest for the de novo detection of full length LTR retrotransposons in large sequence sets. LTRharvest efficiently delivers high quality annotations based on known LTR transposon features like length, distance, and sequence motifs. A quality validation of LTRharvest against a gold standard annotation for Saccharomyces cerevisae and Drosophila melanogaster shows a sensitivity of up to 90% and 97% and specificity of 100% and 72%, respectively. This is comparable or slightly better than annotations for previous software tools. The main advantage of LTRharvest over previous tools is (a) its ability to efficiently handle large datasets from finished or unfinished genome projects, (b) its flexibility in incorporating known sequence features into the prediction, and (c) its availability as an open source software.
LTRharvest is an efficient software tool delivering high quality annotation of LTR retrotransposons. It can, for example, process the largest human chromosome in approx. 8 minutes on a Linux PC with 4 GB of memory. Its flexibility and small space and run-time requirements makes LTRharvest a very competitive candidate for future LTR retrotransposon annotation projects. Moreover, the structured design and implementation and the availability as open source provides an excellent base for incorporating novel concepts to further improve prediction of LTR retrotransposons.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>18194517</pmid><doi>10.1186/1471-2105-9-18</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Base Sequence Chromosome Mapping - methods Drosophila melanogaster Identification and classification Molecular Sequence Data Programming Languages Retroelements - genetics Retrotransposons Saccharomyces Sequence Alignment - methods Sequence Analysis, DNA - methods Software |
title | LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons |
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