ArticleGenomics, proteomics & bioinformatics2019
Gclust: A Parallel Clustering Tool for Microbial Genomic Data.
Article in Genomics, proteomics & bioinformatics, 2019. 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.
- Clustering methods for categorical time series and sequences : a scoping review.BMC medical research methodology · 2026Article
- Benchmarking the impact of reference genome selection on taxonomic profiling accuracy.BMC genomics · 2026Article
- Article
- Targeted IS-element sequencing uncovers transposition dynamics during selective pressure in enterococci.PLoS pathogens · 2023Article
- RabbitTClust: enabling fast clustering analysis of millions of bacteria genomes with MinHash sketches.Genome biology · 2023Article
- Long-read sequencing of 111 rice genomes reveals significantly larger pan-genomes.Genome research · 2022Article
Corrections and comments
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Authors and funding
18 authors.
Funding
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Abstract
The accelerating growth of the public microbial genomic data imposes substantial burden on the research community that uses such resources. Building databases for non-redundant reference sequences from massive microbial genomic data based on clustering analysis is essential. However, existing clustering algorithms perform poorly on long genomic sequences. In this article, we present Gclust, a parallel program for clustering complete or draft genomic sequences, where clustering is accelerated with a novel parallelization strategy and a fast sequence comparison algorithm using sparse suffix arrays (SSAs). Moreover, genome identity measures between two sequences are calculated based on their maximal exact matches (MEMs). In this paper, we demonstrate the high speed and clustering quality of Gclust by examining four genome sequence datasets. Gclust is freely available for non-commercial use at https://github.com/niu-lab/gclust. We also introduce a web server for clustering user-uploaded genomes at http://niulab.scgrid.cn/gclust.
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Registered trials
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