bioRxivBioinformaticsPreprint
TrEMOLO: Accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
Mourdas MohamediD, François SabotiD, Marion Varoqui, Bruno MugatiD, Katell AudouiniD, Alain Pélisson, Anna-Sophie Fiston-LavieriD, Séverine ChambeyroniD
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.
- assay: long-read sequencing
- research focus: variant calling
- research focus: software / tool
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 3
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