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KmerGO: A Tool to Identify Group-Specific Sequences With k-mers

Capturing group-specific sequences between two groups of genomic/metagenomic sequences is critical for the follow-up identifications of singular nucleotide variants (SNVs), gene families, microbial species or other elements associated with each group. A sequence that is present, or rich, in one grou...

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Detalles Bibliográficos
Autores principales: Wang, Ying, Chen, Qi, Deng, Chao, Zheng, Yiluan, Sun, Fengzhu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7477287/
https://www.ncbi.nlm.nih.gov/pubmed/32983048
http://dx.doi.org/10.3389/fmicb.2020.02067
Descripción
Sumario:Capturing group-specific sequences between two groups of genomic/metagenomic sequences is critical for the follow-up identifications of singular nucleotide variants (SNVs), gene families, microbial species or other elements associated with each group. A sequence that is present, or rich, in one group, but absent, or scarce, in another group is considered a “group-specific” sequence in our study. We developed a user-friendly tool, KmerGO, to identify group-specific sequences between two groups of genomic/metagenomic long sequences or high-throughput sequencing datasets. Compared with other tools, KmerGO captures group-specific k-mers (k up to 40 bps) with much lower requirements for computing resources in much shorter running time. For a 1.05 TB dataset (.fasta), it takes KmerGO about 21.5 h (including k-mer counting) to return assembled group-specific sequences on a regular stand-alone workstation with no more than 1 GB memory. Furthermore, KmerGO can also be applied to capture trait-associated sequences for continuous-trait. Through multi-process parallel computing, KmerGO is implemented with both graphic user interface and command line on Linux and Windows free from any pre-installed supporting environments, packages, and complex configurations. The output group-specific k-mers or sequences from KmerGO could be the inputs of other tools for the downstream discovery of biomarkers, such as genetic variants, species, or genes. KmerGO is available at https://github.com/ChnMasterOG/KmerGO.