MyTaxa: an advanced taxonomic classifier for genomic and metagenomic sequences

By Chengwei Luo, L. Rodriguez-R., Konstantinos T. Konstantinidis. Nucleic Acids Research, 2014

532 citations recorded by the source corpus.

Determining the taxonomic affiliation of sequences assembled from metagenomes remains a major bottleneck that affects research across the fields of environmental, clinical and evolutionary microbiology. Here, we introduce MyTaxa, a homology-based bioinformatics framework to classify metagenomic and genomic sequences with unprecedented accuracy. The distinguishing aspect of MyTaxa is that it employs all genes present in an unknown sequence as classifiers, weighting each gene based on its (predetermined) classifying power at a given taxonomic level and frequency of horizontal gene transfer. MyTaxa also implements a novel classification scheme based on the genome-aggregate average amino acid identity concept to determine the degree of novelty of sequences representing uncharacterized taxa, i.e. whether they represent novel species, genera or phyla. Application of MyTaxa on in silico generated (mock) and real metagenomes of varied read length (100–2000 bp) revealed that it correctly classified at least 5% more sequences than any other tool. The analysis also showed that ∼10% of the assembled sequences from human gut metagenomes represent novel species with no sequenced representatives, several of which were highly abundant in situ such as members of the Prevotella genus. Thus, MyTaxa can find several important applications in microbial identification and diversity studies.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/7c9729342d19b205cf6dd0dbe9f756378f78582d

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Citations in the corpus

The Microbial Genomes Atlas (MiGA) webserver: taxonomic and gene diversity analysis of Archaea and Bacteria at the whole genome level (2018, background): “MyTaxa scan traverses the genome sequence in windows of ten genes and compares the taxonomic affiliations predicted by MyTaxa (18), flagging regions with unexpectedly large Hellinger distances to the genome-wide distribution (19).”
SqueezeMeta, A Highly Portable, Fully Automatic Metagenomic Analysis Pipeline (2018, unknown): “These thresholds are 85, 60, 55, 50, 46, 42 and 40% for species, genus, family, order, class, phylum and superkingdom ranks, respectively (Luo et al., 2014).”
Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing (2015, unknown): “How ever, WGS is more expensive and requires more extensive data analysis [10, 20-22].”