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bioRxiv · 10.1101/2022.07.21.500944

TrEMOLO: Accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches

Mohamed, M.·Sabot, F.·Varoqui, M.·Mugat, B.·Audouin, K.·Pelisson, A.·Fiston-Lavier, A.-S.·Chambeyron, S.
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Abstract

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/DrosophilaGenomeEvolution/TrEMOLO.

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Mohamed, M., Sabot, F., Varoqui, M., Mugat, B., Audouin, K., Pelisson, A., Fiston-Lavier, A.-S., Chambeyron, S.. 2022-07-22. TrEMOLO: Accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches. https://doi.org/10.1101/2022.07.21.500944

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