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ABSTRACT: Background
The problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step.Results
Using both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining or increasing N50 and N75. Moreover, BIGMAC shows the largest N75 to number of mis-assemblies ratio on all tested datasets when compared to other post-processing tools.Conclusions
BIGMAC demonstrates the effectiveness of the post-processing approach in improving the quality of metagenomic assemblies.
SUBMITTER: Lam KK
PROVIDER: S-EPMC5084376 | biostudies-literature | 2016 Oct
REPOSITORIES: biostudies-literature
BMC bioinformatics 20161028 1
<h4>Background</h4>The problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step.<h4>Results</h4>Using both the assembled contigs and original long reads as input, BIGMAC first breaks ...[more]