ArticleBMC genomics2018
iMGEins: detecting novel mobile genetic elements inserted in individual genomes.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- DeepMobilome: predicting mobile genetic elements using sequencing reads of microbiomes.Briefings in bioinformatics · 2025Article
- Identifying and tracking mobile elements in evolving compost communities yields insights into the nanobiome.ISME communications · 2023Article
- Human Retrotransposons and Effective Computational Detection Methods for Next-Generation Sequencing Data.Life (Basel, Switzerland) · 2022Review
- A Map of 3' DNA Transduction Variants Mediated by Non-LTR Retroelements on 3202 Human Genomes.Biology · 2022Article
- The Gut Microbiome as a Reservoir for Antimicrobial Resistance.The Journal of infectious diseases · 2021Review
- Experimental approaches to tracking mobile genetic elements in microbial communities.FEMS microbiology reviews · 2020Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundRecent advances in sequencing technology have allowed us to investigate personal genomes to find structural variations, which have been studied extensively to identify their association with the physiology of diseases such as cancer. In particular, mobile genetic elements (MGEs) are one of the major constituents of the human genomes, and cause genome instability by insertion, mutation, and rearrangement.
resultWe have developed a new program, iMGEins, to identify such novel MGEs by using sequencing reads of individual genomes, and to explore the breakpoints with the supporting reads and MGEs detected. iMGEins is the first MGE detection program that integrates three algorithmic components: discordant read-pair mapping, split-read mapping, and insertion sequence assembly. Our evaluation results showed its outstanding performance in detecting novel MGEs from simulated genomes, as well as real personal genomes. In detail, the average recall and precision rates of iMGEins are 96.67 and 100%, respectively, which are the highest among the programs compared. In the testing with real human genomes of the NA12878 sample, iMGEins shows the highest accuracy in detecting MGEs within 20 bp proximity of the breakpoints annotated.
conclusionIn order to study the dynamics of MGEs in individual genomes, iMGEins was developed to accurately detect breakpoints and report inserted MGEs. Compared with other programs, iMGEins has valuable features of identifying novel MGEs and assembling the MGEs inserted.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.