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This package is developed for automated whole-genome de-novo TE annotation and benchmarking the annotation performance of TE libraries.

For the initial search of TE candidates, LTRharvest, LTR_FINDER_parallel, and LTR_retriever are incorporated in this package to identify LTR retrotransposons; GenericRepeatFinder, TIR-Learner, and MITE-Hunter are incorporated in this package to identify TIR transposons (a subclass of DNA transposons); HelitronScanner is incorporated in this package to identify Helitron transposons (a subclass of DNA transposons); and finally RepeatModeler is used to identify any TEs missed by these structure-based programs (such as SINEs and LINEs).

The EDTA package was designed to filter out false discoveries in raw TE candidates and generate a high-quality non-redundant TE library for whole-genome TE annotations. Selection of initial search programs were based on benckmarkings on the annotation performance using a manually curated TE library in the rice genome.

For benchmarking of a testing TE library, I have provided the curated TE annotation (v6.9.5) for the rice genome (TIGR7/MSU7 version). You may use the lib-test.pl script to compare the annotation performance of your method/library to the methods we have tested (usage shown below).

Environment Modules

Run module spider edta to find out what environment modules are available for this application.

System Variables

  • HPC_EDTA_DIR - installation directory
  • HPC_EDTA_BIN - executable directory


If you publish research that uses edta you have to cite it as follows:

Ou S., Su W., Liao Y., Chougule K., Agda J. R. A., Hellinga A. J., Lugo C. S. B., Elliott T. A., Ware D., Peterson T., Jiang N.✉, Hirsch C. N.✉ and Hufford M. B.✉ (2019). Benchmarking Transposable Element Annotation Methods for Creation of a Streamlined, Comprehensive Pipeline. Genome Biol. 20(1): 275.