Assessment of k-mer spectrum applicability for metagenomic dissimilarity analysis

BMC Bioinformatics
Veronika B DubinkinaDmitry G Alexeev

Abstract

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. We developed a method for calculating pairwise dissimilarity (beta-diversity) of "shotgun" metagenomes based on short k-mer spectra (5 ≤ k ≤ 11). The method was validated on simulated metagenomes and further applied to a large collection of human gut metagenomes from the populations of the world (n=281)....Continue Reading

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Citations

Jun 14, 2017·GigaScience·Anna PhilipsMarek Figlerowicz
Nov 2, 2017·Bioinformatics·Evgenii I OlekhnovichAlexander V Tyakht
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Datasets Mentioned

BETA
SRS062427

Methods Mentioned

BETA
biopsy
feature extraction

Software Mentioned

FASTQ Quality Filter
Metahit
BLASTx
random
UniFrac
MetaPhlAn
DIAMOND MEGAN
- Toolkit
+ MEGAN
DIAMOND

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