Metaxa
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Application data |
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| Created by | Bengtsson J, Eriksson KM, Hartmann M, Nilsson RH |
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| Biological application domain(s) | Metagenomics, Phylogenetics, Sequence analysis, Community analysis |
| Principal bioinformatics method(s) | Hidden Markov Model, Sequence analysis |
| Technology | 454, ABI SOLiD, Illumina, Ion Torrent, Sanger |
| Created at | University of Gothenburg |
| Maintained? | Yes |
| Input format(s) | FASTA |
| Output format(s) | FASTA, Tab-delimited file, Summary |
| Programming language(s) | Perl |
| Licence | GPLv3 |
| Operating system(s) | Linux, UNIX, Mac OS X |
Summary: Metaxa uses Hidden Markov Models to identify, extract and classify small-subunit (SSU) rRNA sequences (12S/16S/18S) of bacterial, archaeal, eukaryotic, chloroplast and mitochondrial origin in metagenomes and other large sequence sets
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Description
The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. In addition to being present in the nucleus of eukaryotes and the core genome of prokaryotes, the gene is also found in the mitochondria of eukaryotes and in the chloroplasts of photosynthetic eukaryotes. These three sets of genes are conceptually paralogous and should in most situations not be aligned and analyzed jointly. To identify the origin of SSU sequences in complex sequence datasets has previously been a time-consuming and largely manual undertaking, and Metaxa aims to remedy this situation. Metaxa is an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin. Metaxa detects and scores SSU sequences for origin with very low proportions of false positives and negatives and is a useful tool in microbial and evolutionary ecology as well as in metagenomics.
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