Name
Abstract | ||
|---|---|---|
Motivation: Species identification and quantification are common tasks in metagenomics and pathogen detection studies. The most recent techniques are built on mapping the sequenced reads against a reference database (e.g. whole genomes, marker genes, proteins) followed by application-dependent analysis steps. Although these methods have been proven to be useful in many scenarios, there is still room for improvement in species and strain level detection, mainly for low abundant organisms. Results: We propose a new method: DUDes, a reference-based taxonomic profiler that introduces a novel top-down approach to analyze metagenomic Next-generation sequencing (NGS) samples. Rather than predicting an organismpresence in the sample based only on relative abundances, DUDes first identifies possible candidates by comparing the strength of the readmapping in each node of the taxonomic tree in an iterativemanner. Instead of using the lowest common ancestor we propose a new approach: the deepest uncommon descendent. We showed in experiments that DUDes works for single andmultiple organisms and can identify lowabundant taxonomic groupswith high precision. Availability and Implementation: DUDes is open source and it is available at http://sf.net/p/dudes |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1093/bioinformatics/btw150 | BIOINFORMATICS |
Field | DocType | Volume |
Genome,Data mining,Lowest common ancestor,Reference database,Computer science,Species identification,Metagenomics,Computational biology,Taxonomic rank | Journal | 32 |
Issue | ISSN | Citations |
15 | 1367-4803 | 3 |
PageRank | References | Authors |
0.39 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vitor Piro | 1 | 3 | 0.73 |
| Martin S Lindner | 2 | 20 | 2.63 |
| Bernhard Y. Renard | 3 | 89 | 11.65 |