Abstract
Nowadays a widely production and low cost of sequencing has allowed the extension of metagenomics in order to explore the genomic information from diverse environments. This offers the opportunity to examine new approaches for sequence binning and functional assignment. Driving of metagenomic studies using high throughput sequencing, usually follows the same pipeline used to analyze single genomes: sequence assembling, gene prediction, functional annotation and phylogenetic classification of reads, contigs or scaffolds, nevertheless, the accuracy of this approach is limited by the length of the reads or resulting contigs.
In Silico Hybridization System is an approach of functional and taxonomical assignment. It has default assignment at gender taxonomic level binning. This tool works with two general pipelines: Probes Creator (CrSo), ordered to design DNA probes (fingerprints) to gender taxonomic level and Sequential In silico Hybridator (HISS) which use the probes to make the hybridization with the community reads.
This bioinformatics tool allows characterization of the microbial metabolism in charge of biogeochemical cycles, tracking their key stages using debugged reference information. This strategy resulted in an increasing of binning accuracy. The simulated and real scenarios were better described using one probe and selection threshold fitted to a logarithmic distribution, with mean sensitivity of 85% and mean specificity of 83%.
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Torres-Estupiñan, G.G., Barreto-Hernández, E. (2014). In Silico Hybridization System for Mapping Functional Genes of Soil Microorganism Using Next Generation Sequencing. In: Castillo, L., Cristancho, M., Isaza, G., Pinzón, A., Rodríguez, J. (eds) Advances in Computational Biology. Advances in Intelligent Systems and Computing, vol 232. Springer, Cham. https://doi.org/10.1007/978-3-319-01568-2_48
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DOI: https://doi.org/10.1007/978-3-319-01568-2_48
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