Analyzing Metabolite Profiles and Microbial Abundances

The generalized linear model procedure was used to analyze the metabolites concentration and production using the SPSS 21.0 software (SPSS Inc., Chicago, IL). When sampling time was included in the model, a linear mixed model was used with treatment, sampling time, and the treatment by sampling time interaction as fixed effects and the animal as a random factor. The ANCOM-BC R package was used to determine the differentially abundant taxa for amplicon and metagenome data [96 (link)]. The Wilcoxon rank-sum test in the JMP Pro software (JMP Pro version 13.2.1, SAS Institute Inc., SAS Institute, Cary, NC) was used to analyze the relative abundance of functional genes and MAGs. All P-values were adjusted for false discovery rate using the Benjamini–Hochberg method, and P < .05 was regarded as statistically significant.

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Li Q., Ma Z., Huo J., Zhang X., Wang R., Zhang S., Jiao J., Dong X., Janssen P.H., Ungerfeld E.M., Greening C., Tan Z, & Wang M. (2024). Distinct microbial hydrogen and reductant disposal pathways explain interbreed variations in ruminant methane yield. The ISME Journal, 18(1), wrad016.

Publication 2024

JMP Pro

Corresponding Organization :

Other organizations : University of Chinese Academy of Sciences, Chinese Academy of Sciences, Institute of Subtropical Agriculture, Lanzhou University, Ministry of Natural Resources, Fujian Institute of Oceanography, AgResearch, Instituto de Investigaciones Agropecuarias, Australian Regenerative Medicine Institute, Monash University

Top 5 similar protocols

Variable analysis

independent variables

Treatment
Sampling time

dependent variables

Metabolites concentration
Metabolites production
Differentially abundant taxa for amplicon and metagenome data
Relative abundance of functional genes
Relative abundance of MAGs

control variables

Animal

controls

No positive or negative controls were explicitly mentioned.

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