2-AIN-505, 2-AIN-251: Seminár z bioinformatiky (1) a (3)
Zima 2019
Abstrakt

Veronika B. Dubinkina, Dmitry S. Ischenko, Vladimir I. Ulyantsev, Alexander V. Tyakht, Dmitry G. Alexeev. Assessment of k-mer spectrum applicability for metagenomic dissimilarityanalysis. BMC bioinformatics, 17:38. 2016.

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Download from publisher: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0875-7 PubMed

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Abstract:

BACKGROUND: A rapidly increasing flow of genomic data requires the development of
efficient methods for obtaining its compact representation. Feature extraction
facilitates classification, clustering and model analysis for testing and
refining biological hypotheses. \"Shotgun\" metagenome is an analytically
challenging type of genomic data - containing sequences of all genes from the
totality of a complex microbial community. Recently, researchers started to
analyze metagenomes using reference-free methods based on the analysis of
oligonucleotides (k-mers) frequency spectrum previously applied to isolated
genomes. However, little is known about their correlation with the existing
approaches for metagenomic feature extraction, as well as the limits of
applicability. Here we evaluated a metagenomic pairwise dissimilarity measure
based on short k-mer spectrum using the example of human gut microbiota, a
biomedically significant object of study. RESULTS: We developed a method for
calculating pairwise dissimilarity (beta-diversity) of \"shotgun\" metagenomes
based on short k-mer spectra (5