Metabolite Set Enrichment Analysis for Loadings

Computing metabolite set enrichment analysis (MSEA) (Yamamoto, H. et al. (2014) ), single sample enrichment analysis (SSEA) (Yamamoto, H. (2023) ) and over-representation analysis (ORA) that accounts for undetected metabolites (Yamamoto, H. (2024) ).

mseapca

Metabolite set enrichment analysis for loadings

mseapca provides functions for metabolite set enrichment analysis with loading in principal component anaysis and partial least squares, and single sample enrichment analysis.

• Metabolite set enrichment analysis [1] can be performed using the "msea_ora" or "msea_sub" functions.

• Our mseapca package utilizes the loadings package ( https://cran.r-project.org/web/packages/loadings ) to conduct multivariate analyses like PCA and PLS, along with their respective loadings.

• The "ssea_ora" function can be used to compute single sample enrichment analysis based on over-representation analysis [2].

• The "msea_ora" function performs over-representation analysis while accounting for undetected metabolites [3].

• The "msea_ora_range" function estimates the possible range of p-values under uncertainty caused by undetected metabolites [3].

References
[1] Yamamoto H. et al., BMC Bioinformatics, (2014) 15(1):51. doi: https://doi.org/10.1186/1471-2105-15-51
[2] Yamamoto H. , Jxiv, (2023). doi: https://doi.org/10.51094/jxiv.484 [3] Yamamoto H. , Jxiv, (2024). doi: https://doi.org/10.51094/jxiv.954

Installation (in preparation)

The latest stable version can be installed from CRAN:

install.packages("mseapca")

The latest development version can be installed from GitHub:

# install.packages("devtools")
devtools::install_github("hiroyukiyamamoto/mseapca")