SWIF-TE: identifying novel transposable element insertions from short read data
Claire C. MenardiD, Nathan S. CatliniD, Adrian E. PlattsiD, Yinjie QiuiD, Emma Y. RobackiD, Manisha MunasingheiD, Nathan M. SpringeriD, Emily B. JosephsiD, Candice N. HirschiD
Abstract
Transposable element (TE) insertion polymorphisms (TIPs) are TEs not in the same location between individuals. TIPs have contributed to genomic and phenomic variation but have been historically difficult to study due to their repetitive nature. Here, we describe a fast and memory-efficient tool to identify novel TIPs from short read sequences. SWIF-TE was able to identify 1,438 insertions at a precision rate of 27% using 0.10 Gb of memory and 0.82 hours of runtime from 15x resequencing data of a non-reference maize inbred. SWIF-TE is a powerful tool for studying TE variation in species with TE-rich genomes.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 1
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Efficient detection of transposable element insertion polymorphisms between genomes using short-read sequencing data
Pierre Baduel, Leandro Quadrana, Vincent Colot·Methods in molecular biologyPeer-reviewed·Jan 1, 2021
- Ultra-Sensitive Detection of Transposon Insertions Across Multiple Families by Transposable Element Display Sequencing
Pol Vendrell‐Mir, Basile Leduque, Leandro Quadrana·Genome biologyPeer-reviewed·Mar 6, 2025
- Whole Genome Variation of Transposable Element Insertions in a Maize Diversity Panel
Y. Qiu, C. O'Connor, … C. Hirsch·bioRxiv·Sep 25, 2020
- A Unified Framework to Analyze Transposable Element Insertion Polymorphisms using Genome-graphs
Cristian Groza, Xun Chen, … Clément Goubert·Nature CommunicationsPeer-reviewed·Oct 16, 2024
- McClintock: An integrated pipeline for detecting transposable element insertions in whole genome shotgun sequencing data.
Michael G. Nelson, Raquel S. Linheiro, Casey Bergman·G3 Genes Genomes GeneticsPeer-reviewed·Jun 21, 2017
- HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data
Dhawal S. Jain, Chong Chu, … Peter J. Park·BioinformaticsPeer-reviewed·Oct 17, 2020