Microbial Biomarkers for Colorectal Cancer Identified with Random Forest Model

Combining p-values from various statistical methods for microbiome data

MOTIVATION

In the field of microbiome analysis, there exist various statistical methods that have been developed for identifying differentially expressed features, that account for the overdispersion and the high sparsity of microbiome data. However, due to the differences in statistical models or test formulations, it is quite often to have inconsistent significance results across statistical methods, that makes it difficult to determine the importance of microbiome taxa. Thus, it is practically important to have the integration of the result from all statistical methods to determine the importance of microbiome taxa. A standard meta-analysis is a powerful tool for integrative analysis and it provides a summary measure by combining p-values from various statistical methods. While there are many meta-analyses available, it is not easy to choose the best meta-analysis that is the most suitable for microbiome data.

RESULTS

In this study, we investigated which meta-analysis method most adequately represents the importance of microbiome taxa. We considered Fisher's method, minimum value of p method, Simes method, Stouffer's method, Kost method, and Cauchy combination test. Through simulation studies, we showed that Cauchy combination test provides the best combined value of p in the sense that it performed the best among the examined methods while controlling the type 1 error rates. Furthermore, it produced high rank similarity with the true ranks. Through the real data application of colorectal cancer microbiome data, we demonstrated that the most highly ranked microbiome taxa by Cauchy combination test have been reported to be associated with colorectal cancer.

Interaction of environmental eukaryotic microorganisms and fungi in the pond-cultured carps: new insights into the potential pathogenic fungi in the freshwater aquaculture

The quality and safety of the aquatic products have gradually become the focus of global attention. In this study, the environmental eukaryotic and fungi communities in pond-cultured grass carp (Ctenopharyngodon idellus) and the koi carp (Cyprinus carpio L.) were investigated. For comparative analysis, the alpha diversity shows that the environmental microbial abundance in the koi carp groups were higher than that in the grass carp groups, while beta diversity reveals that the differences of the microbial community composition and structures in the grass carp groups were significantly higher than those in the koi carp groups. Meanwhile, the environmental microbial diversity of grass carp groups was higher than that of koi carp groups at phylum level, but showed no significant difference at genus level. Additionally, the dominant total phyla were Opisthokonta, Stramenopiles plusAlveolates plusRhizaria, Archaeplastida, Cryptophyceae, and Centrohelida for the 18S rRNA gene and Ciliophora, Chlorophyta, and Ascomycota for the ITS2 rRNA gene in both of the two carp groups. Additionally, annotation analysis showed that the biomarkers in the grass carp groups are significantly higher than those of the koi carp groups. Furthermore, the functional prediction of Funguild showed significant difference in outputs, while similarity in trophic modes and guild types between the two carp groups. Meanwhile, the total relative abundances of animal pathogen, fungal parasite, and plant pathogen were extremely similar between the two carp groups. Surprisingly, one pathogenic fungus of genus Fusarium was identified in both the environments of two carp groups based on filtered operational taxonomic unit tables. Overall, this is the first robust report to understand the characteristics of environmental eukaryotic microorganisms and fungi in the edible and ornamental carps. Our results also provide the basic data for the prevention of fungal diseases and the healthy culture of the carps.