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Analysis of Gut Microbiome Structure Based on GMPR+Spectrum.

Authors :
Xiong, Xin
Ren, Yuyan
He, Jianfeng
Source :
Applied Sciences (2076-3417); Jun2022, Vol. 12 Issue 12, p5895, 23p
Publication Year :
2022

Abstract

The gut microbiome is related to many major human diseases, and it is of great significance to study the structure of the gut microbiome under different conditions. Multivariate statistics or pattern recognition methods were often used to identify different structural patterns in gut microbiome data. However, these methods have some limitations. Minimal hepatic encephalopathy (MHE) datasets were taken as an example. Due to the physical lack or insufficient sampling of the gut microbiome in the sequencing process, the microbiome data contains many zeros. Therefore, the geometric mean of pairwise ratios (GMPR) was used to normalize gut microbiome data, then Spectrum was used to analyze the structure of the gut microbiome, and lastly, the structure of core microflora was compared with Network analysis. GMPR calculates the Intraclass correlation coefficient (ICC), whose reproducibility was significantly better than other normalization methods. In addition, running-time, Normalized Mutual Information (NMI), Davies-Boulding Index (DBI), and Calinski-Harabasz index (CH) of GMPR+Spectrum were far superior to other clustering algorithms such as M3C, iClusterPlus. GMPR+Spectrum can not only perform better but also effectively identify the structural differences of intestinal microbiota in different patients and excavate the unique critical bacteria such as Akkermansia, and Lactobacillus in MHE patients, which may provide a new reference for the study of the gut microbiome in disease. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
12
Issue :
12
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
157639700
Full Text :
https://doi.org/10.3390/app12125895