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

被引:0
|
作者
Mourdas Mohamed
François Sabot
Marion Varoqui
Bruno Mugat
Katell Audouin
Alain Pélisson
Anna-Sophie Fiston-Lavier
Séverine Chambeyron
机构
[1] Institute of Human Genetics,
[2] UMR9002,undefined
[3] CNRS and Université de Montpellier,undefined
[4] DIADE,undefined
[5] University of Montpellier,undefined
[6] CIRAD,undefined
[7] IRD,undefined
[8] IFB - Southgreen Bioversity,undefined
[9] CIRAD,undefined
[10] INRAE,undefined
[11] IRD,undefined
[12] TAGC,undefined
[13] UMR 1090 INSERM,undefined
[14] ISEM,undefined
[15] Université Montpellier,undefined
[16] CNRS,undefined
[17] IRD,undefined
[18] CIRAD,undefined
[19] EPHE,undefined
[20] Institut Universitaire de France (IUF),undefined
来源
关键词
Genome; Software; Transposable element calling; Long-read DNA sequencing; Nanopore sequencing; Transposable element allelic frequency; Haplotypes; Structural variation;
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学科分类号
摘要
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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