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- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data
- 2013
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Ingår i: Methods in Ecology and Evolution. - 2041-210X. ; 4:10, s. 914-919
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Tidskriftsartikel (refereegranskat)abstract
- The nuclear ribosomal internal transcribed spacer (ITS) region is the primary choice for molecular identification of fungi. Its two highly variable spacers (ITS1 and ITS2) are usually species specific, whereas the intercalary 5.8S gene is highly conserved. For sequence clustering and blast searches, it is often advantageous to rely on either one of the variable spacers but not the conserved 5.8S gene. To identify and extract ITS1 and ITS2 from large taxonomic and environmental data sets is, however, often difficult, and many ITS sequences are incorrectly delimited in the public sequence databases. We introduce ITSx, a Perl-based software tool to extract ITS1, 5.8S and ITS2 – as well as full-length ITS sequences – from both Sanger and high-throughput sequencing data sets. ITSx uses hidden Markov models computed from large alignments of a total of 20 groups of eukaryotes, including fungi, metazoans and plants, and the sequence extraction is based on the predicted positions of the ribosomal genes in the sequences. ITSx has a very high proportion of true-positive extractions and a low proportion of false-positive extractions. Additionally, process parallelization permits expedient analyses of very large data sets, such as a one million sequence amplicon pyrosequencing data set. ITSx is rich in features and written to be easily incorporated into automated sequence analysis pipelines. ITSx paves the way for more sensitive blast searches and sequence clustering operations for the ITS region in eukaryotes. The software also permits elimination of non-ITS sequences from any data set. This is particularly useful for amplicon-based next-generation sequencing data sets, where insidious non-target sequences are often found among the target sequences. Such non-target sequences are difficult to find by other means and would contribute noise to diversity estimates if left in the data set.
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| 2. |
- Sanli, Kemal, et al.
(författare)
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FANTOM: Functional and taxonomic analysis of metagenomes
- 2013
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- Background Interpretation of quantitative metagenomics data is important for our understanding of ecosystem functioning and assessing differences between various environmental samples. There is a need for an easy to use tool to explore the often complex metagenomics data in taxonomic and functional context. Results Here we introduce FANTOM, a tool that allows for exploratory and comparative analysis of metagenomics abundance data integrated with metadata information and biological databases. Importantly, FANTOM can make use of any hierarchical database and it comes supplied with NCBI taxonomic hierarchies as well as KEGG Orthology, COG, PFAM and TIGRFAM databases. Conclusions The software is implemented in Python, is platform independent, and is available at http://www.sysbio.se/Fantom.
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