Abstract

Abstract Motivation: Next-generation sequencing allows us to sequence reads from a microbial environment using single-cell sequencing or metagenomic sequencing technologies. However, both technologies suffer from the problem that sequencing depth of different regions of a genome or genomes from different species are highly uneven. Most existing genome assemblers usually have an assumption that sequencing depths are even. These assemblers fail to construct correct long contigs. Results: We introduce the IDBA-UD algorithm that is based on the de Bruijn graph approach for assembling reads from single-cell sequencing or metagenomic sequencing technologies with uneven sequencing depths. Several non-trivial techniques have been employed to tackle the problems. Instead of using a simple threshold, we use multiple depthrelative thresholds to remove erroneous k-mers in both low-depth and high-depth regions. The technique of local assembly with paired-end information is used to solve the branch problem of low-depth short repeat regions. To speed up the process, an error correction step is conducted to correct reads of high-depth regions that can be aligned to highconfident contigs. Comparison of the performances of IDBA-UD and existing assemblers (Velvet, Velvet-SC, SOAPdenovo and Meta-IDBA) for different datasets, shows that IDBA-UD can reconstruct longer contigs with higher accuracy. Availability: The IDBA-UD toolkit is available at our website http://www.cs.hku.hk/~alse/idba_ud Contact: chin@cs.hku.hk

Keywords

ContigMetagenomicsDe Bruijn graphSequence assemblyHybrid genome assemblyComputer scienceDNA sequencingk-merDeep sequencingGenomeComputational biologyReference genomeDe Bruijn sequenceNanopore sequencingBiologyAlgorithmGraphGeneticsTheoretical computer scienceMathematicsGene

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Publication Info

Year
2012
Type
article
Volume
28
Issue
11
Pages
1420-1428
Citations
3099
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Closed

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Yu Peng, Henry C. M. Leung, Siu‐Ming Yiu et al. (2012). IDBA-UD: a <i>de novo</i> assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics , 28 (11) , 1420-1428. https://doi.org/10.1093/bioinformatics/bts174

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DOI
10.1093/bioinformatics/bts174