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Genometa - A Fast and Accurate Classifier for Short Metagenomic Shotgun Reads

  • Metagenomic studies use high-throughput sequence data to investigate microbial communities in situ. However, considerable challenges remain in the analysis of these data, particularly with regard to speed and reliable analysis of microbial species as opposed to higher level taxa such as phyla. We here present Genometa, a computationally undemanding graphical user interface program that enables identification of bacterial species and gene content from datasets generated by inexpensive high-throughput short read sequencing technologies. Our approach was first verified on two simulated metagenomic short read datasets, detecting 100% and 94% of the bacterial species included with few false positives or false negatives. Subsequent comparative benchmarking analysis against three popular metagenomic algorithms on an Illumina human gut dataset revealed Genometa to attribute the most reads to bacteria at species level (i.e. including all strains of that species) and demonstrate similar or better accuracy than the other programs. Lastly, speed was demonstrated to be many times that of BLAST due to the use of modern short read aligners. Our method is highly accurate if bacteria in the sample are represented by genomes in the reference sequence but cannot find species absent from the reference. This method is one of the most user-friendly and resource efficient approaches and is thus feasible for rapidly analysing millions of short reads on a personal computer.

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Author:Colin F. Davenport, Jens Neugebauer, Nils Beckmann, Benedikt Friedrich, Burim Kameri, Svea Kokott, Malte Paetow, Björn Siekmann, Matthias Wieding-Drewes, Markus Wienhöfer, Stefan Wolf, Burkhard Tümmler, Volker AhlersORCiDGND, Frauke SprengelGND
DOI original:https://doi.org/10.1371/journal.pone.0041224
Parent Title (English):PLOS One
Document Type:Article
Year of Completion:2012
Publishing Institution:Hochschule Hannover
Release Date:2016/07/08
Tag:BLAST algorithm; Bacterial genomics; Genomic databases; Metagenomics; Sequence alignment
Page Number:8
Link to catalogue:879454296
Institutes:Fakultät IV - Wirtschaft und Informatik
DDC classes:570 Biowissenschaften, Biologie
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International