LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons

doi:10.1186/1471-2105-9-18

BMC Bioinformatics

Volume 9

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Willhoeft U

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LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons

David Ellinghaus , Stefan Kurtz and Ute Willhoeft

ZBH – Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany

author email corresponding author email

BMC Bioinformatics 2008, 9:18doi:10.1186/1471-2105-9-18


Published:	14 January 2008

Additional files

Additional file 1:

Full description of parameters used and results of the comparison of de novo LTR retrotransposon prediction programs. Additional file 1 includes Table A – list of abbreviations, Table B – Quality validation on the S. cerevisiae genome (complete data) and Table C – Quality validation on the D. melanogaster genome (complete data).

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