Mohamed M., Sabot François, Varoqui M., Mugat B., Audouin K., Pelisson A., Fiston-Lavier A. S., Chambeyron S. (2023). TrEMOLO : accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches. Genome Biology, 24 (1), 63 [20 p.]. ISSN 1474-760X.
Titre du document
TrEMOLO : accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
Transposable Element MOnitoring with LOng-reads (TrEMOLO) is a new software that combines assembly- and mapping-based approaches to robustly detect genetic elements called transposable elements (TEs). Using high- or low-quality genome assemblies, TrEMOLO can detect most TE insertions and deletions and estimate their allele frequency in populations. Benchmarking with simulated data revealed that TrEMOLO outperforms other state-of-the-art computational tools. TE detection and frequency estimation by TrEMOLO were validated using simulated and experimental datasets. Therefore, TrEMOLO is a comprehensive and suitable tool to accurately study TE dynamics. TrEMOLO is available under GNU GPL3.0 at https://github.com/Drosophila GenomeEvolution/TrEMOLO.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020]
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Biotechnologies [084]
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Informatique [122]
