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BIGMAC: Breaking Inaccurate Genomes and Merging Assembled Contigs for long read metagenomic assembly

Ka-Kit Lam, Richard Hall, Alicia Clum, Satish Rao
doi: https://doi.org/10.1101/045690
Ka-Kit Lam
1Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, the USA.
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Richard Hall
2Pacific Biosciences, Menlo Park, the USA.
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Alicia Clum
3Joint Genome Institute, Walnut Creek, the USA.
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Satish Rao
1Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, the USA.
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  • For correspondence: satishr@cs.berkeley.edu
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Abstract

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. 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/increasing N50 and N75. The software is available at https://github.com/kakitone/BIGMAC

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted March 29, 2016.
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BIGMAC: Breaking Inaccurate Genomes and Merging Assembled Contigs for long read metagenomic assembly
Ka-Kit Lam, Richard Hall, Alicia Clum, Satish Rao
bioRxiv 045690; doi: https://doi.org/10.1101/045690
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BIGMAC: Breaking Inaccurate Genomes and Merging Assembled Contigs for long read metagenomic assembly
Ka-Kit Lam, Richard Hall, Alicia Clum, Satish Rao
bioRxiv 045690; doi: https://doi.org/10.1101/045690

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