ArticleBioinformatics (Oxford, England)2016
Compacting de Bruijn graphs from sequencing data quickly and in low memory.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers.
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103 citing papers in PubMed.
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- META-DIFF: a k-mer-based pipeline that detects differentially abundant sequences in metagenomics whole genome sequencing.Scientific reports · 2026Article
- GnnDebugger: GNN based error correction in De Bruijn Graphs.BMC bioinformatics · 2026Article
- GATHeR: graph-based accurate tool for immunoglobulin heavy- and light-chain reconstruction.Nature communications · 2026Article
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- A pangenome and pantranscriptome of hexaploid oat.Nature · 2026Article
- DVOUG enables robust DNA sequence assembly and reconstruction with a dynamic, variable-order graph.Cell reports methods · 2025Article
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- Comparative metagenomics using pan-metagenomic graphs.bioRxiv : the preprint server for biology · 2025Article
- Non-adaptive Radiation Promotes Phenotypic Diversification and Convergent Evolution of Aposematic Mimicry in a Highly Diverse Genus of Megaloptera.Systematic biology · 2025Article
- Logan: Planetary-Scale Genome Assembly Surveys Life's Diversity.bioRxiv : the preprint server for biology · 2025Article
- Sama: a contig assembler with correctness guarantee.Algorithms for molecular biology : AMB · 2025Article
- A scalable distributed pipeline for reference-free variants calling.BMC genomics · 2025Article
- Review
- Efficient and robust search of microbial genomes via phylogenetic compression.Nature methods · 2025Article
43 more citing papers are in PubMed but not listed here.
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
motivationAs the quantity of data per sequencing experiment increases, the challenges of fragment assembly are becoming increasingly computational. The de Bruijn graph is a widely used data structure in fragment assembly algorithms, used to represent the information from a set of reads. Compaction is an important data reduction step in most de Bruijn graph based algorithms where long simple paths are compacted into single vertices. Compaction has recently become the bottleneck in assembly pipelines, and improving its running time and memory usage is an important problem.
resultsWe present an algorithm and a tool bcalm 2 for the compaction of de Bruijn graphs. bcalm 2 is a parallel algorithm that distributes the input based on a minimizer hashing technique, allowing for good balance of memory usage throughout its execution. For human sequencing data, bcalm 2 reduces the computational burden of compacting the de Bruijn graph to roughly an hour and 3 GB of memory. We also applied bcalm 2 to the 22 Gbp loblolly pine and 20 Gbp white spruce sequencing datasets. Compacted graphs were constructed from raw reads in less than 2 days and 40 GB of memory on a single machine. Hence, bcalm 2 is at least an order of magnitude more efficient than other available methods. AVAILABILITY AND IMPLEMENTATION: Source code of bcalm 2 is freely available at: https://github.com/GATB/bcalm CONTACT: rayan.chikhi@univ-lille1.fr.
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