ArticleScientific reports2016
A novel alignment-free method for detection of lateral genetic transfer based on TF-IDF.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.
- What Has Been Trending in the Research of Polyhydroxyalkanoates? A Systematic Review.Frontiers in bioengineering and biotechnology · 2020Pooled it
- A machine learning framework for interpreting phylogenetic tree patterns in interkingdom horizontal gene transfer.Frontiers in bioinformatics · 2026Article
- What Do We Gain When Tolerating Loss? The Information Bottleneck Wrings Out Recombination.Molecular biology and evolution · 2025Article
- Current state and future prospects of Horizontal Gene Transfer detection.NAR genomics and bioinformatics · 2025Review
- GRAMEP: an alignment-free method based on the maximum entropy principle for identifying SNPs.BMC bioinformatics · 2025Article
- Genetic Transfer in Action: Uncovering DNA Flow in an Extremophilic Microbial Community.Environmental microbiology · 2025Article
- A mapping-free natural language processing-based technique for sequence search in nanopore long-reads.BMC bioinformatics · 2024Article
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- INSIDER: alignment-free detection of foreign DNA sequences.Computational and structural biotechnology journal · 2021Article
- An Integrative Computational Approach for the Prediction of Human-BioMed research international · 2020Article
- Patterns, Profiles, and Parsimony: Dissecting Transcriptional Signatures From Minimal Single-Cell RNA-Seq Output With SALSA.Frontiers in genetics · 2020Article
- The statistical power ofSynthetic and systems biotechnology · 2019Article
- Benchmarking of alignment-free sequence comparison methods.Genome biology · 2019Article
- Alignment-free inference of hierarchical and reticulate phylogenomic relationships.Briefings in bioinformatics · 2019Review
- PanDelos: a dictionary-based method for pan-genome content discovery.BMC bioinformatics · 2018Article
- Alignment-Free Sequence Analysis and Applications.Annual review of biomedical data science · 2018Article
- SSAW: A new sequence similarity analysis method based on the stationary discrete wavelet transform.BMC bioinformatics · 2018Article
- Background Adjusted Alignment-Free Dissimilarity Measures Improve the Detection of Horizontal Gene Transfer.Frontiers in microbiology · 2018Article
- Alignment-free sequence comparison: benefits, applications, and tools.Genome biology · 2017Review
- Robust Inference of Genetic Exchange Communities from Microbial Genomes Using TF-IDF.Frontiers in microbiology · 2017Article
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Authors and funding
3 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Lateral genetic transfer (LGT) plays an important role in the evolution of microbes. Existing computational methods for detecting genomic regions of putative lateral origin scale poorly to large data. Here, we propose a novel method based on TF-IDF (Term Frequency-Inverse Document Frequency) statistics to detect not only regions of lateral origin, but also their origin and direction of transfer, in sets of hierarchically structured nucleotide or protein sequences. This approach is based on the frequency distributions of k-mers in the sequences. If a set of contiguous k-mers appears sufficiently more frequently in another phyletic group than in its own, we infer that they have been transferred from the first group to the second. We performed rigorous tests of TF-IDF using simulated and empirical datasets. With the simulated data, we tested our method under different parameter settings for sequence length, substitution rate between and within groups and post-LGT, deletion rate, length of transferred region and k size, and found that we can detect LGT events with high precision and recall. Our method performs better than an established method, ALFY, which has high recall but low precision. Our method is efficient, with runtime increasing approximately linearly with sequence length.
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