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DIGITAL.CSIC
Article . 2025 . Peer-reviewed
Data sources: DIGITAL.CSIC
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Genome Research
Article . 2025 . Peer-reviewed
Data sources: Crossref
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k-mer approaches for biodiversity genomics

Authors: Katharine M. Jenike; Lucía Campos-Domínguez; Marilou Boddé; José Cerca; Christina N. Hodson; Michael C. Schatz; Kamil S. Jaron;

k-mer approaches for biodiversity genomics

Abstract

The wide array of currently available genomes displays a wonderful diversity in size, composition, and structure and is quickly expanding thanks to several global biodiversity genomics initiatives. However, sequencing of genomes, even with the latest technologies, can still be challenging for both technical (e.g., small physical size, contaminated samples, or access to appropriate sequencing platforms) and biological reasons (e.g., germline-restricted DNA, variable ploidy levels, sex chromosomes, or very large genomes). In recent years,k-mer-based techniques have become popular to overcome some of these challenges. They are based on the simple process of dividing the analyzed sequences (e.g., raw reads or genomes) into a set of subsequences of lengthk, calledk-mers, and then analyzing the frequency or sequences of thosek-mers. Analyses based onk-mers allow for a rapid and intuitive assessment of complex sequencing data sets. Here, we provide a comprehensive review to the theoretical properties and practical applications ofk-mers in biodiversity genomics with a special focus on genome modeling.

Country
Spain
Keywords

Genome, Bioinformatik och beräkningsbiologi, Bioinformatics and Computational Biology, Humans, Animals, Review, Biodiversity, Genomics, Sequence Analysis, DNA

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Top 10%
Green