Abstract
MotivationWhole metagenome shotgun sequencing is a powerful approach for assaying the functional potential of microbial communities. We currently lack tools that efficiently and accurately align DNA reads against protein references, the technique necessary for constructing a functional profile. Here, we present PALADIN—a novel modification of the Burrows-Wheeler Aligner that provides accurate alignment, robust reporting capabilities and orders-of-magnitude improved efficiency by directly mapping in protein space.ResultsWe compared the accuracy and efficiency of PALADIN against existing tools that employ nucleotide or protein alignment algorithms. Using simulated reads, PALADIN consistently outperformed the popular DNA read mappers BWA and NovoAlign in detected proteins, percentage of reads mapped and ontological similarity. We also compared PALADIN against four existing protein alignment tools: BLASTX, RAPSearch2, DIAMOND and Lambda, using empirically obtained reads. PALADIN yielded results seven times faster than the best performing alternative, DIAMOND and nearly 8000 times faster than BLASTX. PALADIN's accuracy was comparable to all tested solutions.Availability and ImplementationPALADIN was implemented in C, and its source code and documentation are available at https://github.com/twestbrookunh/paladinSupplementary information Supplementary data are available at Bioinformatics online.
Highlights
Whole metagenome shotgun sequencing is a powerful approach for assaying the functional potential of microbial communities
To improve the sensitivity with which functional profiling of metagenomics samples is performed, we present PALADIN—an algorithm adapted from the popular BWA11 mapping tool
PALADIN identifies and translates six possible open reading frames within each read, and maps these translated DNA sequence reads to a protein reference allowing for rapid identification of functional metagenomic profiles
Summary
Whole metagenome shotgun sequencing is a powerful approach for assaying the functional potential of microbial communities. To improve the sensitivity with which functional profiling of metagenomics samples is performed, we present PALADIN—an algorithm adapted from the popular BWA11 mapping tool (source code is available at https://github.com/twestbrookunh/paladin, see supplementary note and figure 5 for implementation details). PALADIN identifies and translates six possible open reading frames within each read, and maps these translated DNA sequence reads to a protein reference allowing for rapid identification of functional metagenomic profiles.
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