Bioinformatics strategies for taxonomy independent binning and visualization of sequences in shotgun metagenomics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU121299" target="_blank" >RIV/00216305:26220/16:PU121299 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S2001037016300678" target="_blank" >http://www.sciencedirect.com/science/article/pii/S2001037016300678</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.csbj.2016.11.005" target="_blank" >10.1016/j.csbj.2016.11.005</a>
Alternative languages
Result language
angličtina
Original language name
Bioinformatics strategies for taxonomy independent binning and visualization of sequences in shotgun metagenomics
Original language description
One of main steps in a study of microbial communities is resolving their composition, diversity and function. In the past, these issues were mostly addressed by the use of amplicon sequencing of a target gene because of reasonable price and easier computational postprocessing of the bioinformatic data. With the advancement of sequencing techniques, the main focus shifted to the whole metagenome shotgun sequencing, which allows much more detailed analysis of the metagenomic data, including reconstruction of novel microbial genomes and to gain knowledge about genetic potential and metabolic capacities of whole environments. On the other hand, the output of whole metagenomic shotgun sequencing is mixture of short DNA fragments belonging to various genomes, therefore this approach requires more sophisticated computational algorithms for clustering of related sequences, commonly referred to as sequence binning. There are currently two types of binning methods: taxonomy dependent and taxonomy independent. The first type classifies the DNA fragments by performing a standard homology inference against a reference database, while the latter performs the reference-free binning by applying clustering techniques on features extracted from the sequences. In this review, we describe the strategies within the second approach. Although these strategies do not require prior knowledge, they have higher demands on the length of sequences. Besides their basic principle, an overview of particular methods and tools is provided. Furthermore, the review covers the utilization of the methods in context with the length of sequences and discusses the needs for metagenomic data preprocessing in form of initial assembly prior to binning.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computational and Structural Biotechnology Journal
ISSN
2001-0370
e-ISSN
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Volume of the periodical
15
Issue of the periodical within the volume
1
Country of publishing house
SE - SWEDEN
Number of pages
8
Pages from-to
48-55
UT code for WoS article
000392631200006
EID of the result in the Scopus database
2-s2.0-85002168875