A benchmark of transposon insertion detection tools using real data.

ABSTRACT:

Background

Transposable elements (TEs) are an important source of genomic variability in eukaryotic genomes. Their activity impacts genome architecture and gene expression and can lead to drastic phenotypic changes. Therefore, identifying TE polymorphisms is key to better understand the link between genotype and phenotype. However, most genotype-to-phenotype analyses have concentrated on single nucleotide polymorphisms as they are easier to reliable detect using short-read data. Many bioinformatic tools have been developed to identify transposon insertions from resequencing data using short reads. Nevertheless, the performance of most of these tools has been tested using simulated insertions, which do not accurately reproduce the complexity of natural insertions.

Results

We

SUBMITTER: Vendrell-Mir P 

PROVIDER: S-EPMC6937713 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature