mseapca (version 2.0.3)

msea_sub: MSEA by Subramanian et al.

Description

This function performs metabolite set enrichment analysis implemented in the same fashion as gene set enrichment analysis (Subramanian et al. 2005). In this function, a permutation procedure is performed for a metabolite set rather than class label. This procedure corresponds to a "gene set" of permutation type in GSEA-P software (Subramanian et al. 2007). A leading-edge subset analysis is also undertaken following the standard GSEA procedure.

Usage

msea_sub(M, D, y, maxiter = 1000)

Value

list of normalized enrichment score, p-value and q-value for metabolite set, and the results of leading edge subset

Arguments

M

list of metbolite set name and metabolite IDs

D

data.frame(metabolite ID, data matix)

y

response variable (e.g. PC score)

maxiter

maximum number of iterations in random permutation (default=1000)

Author

Hiroyuki Yamamoto

References

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S. & Mesirov, J. P. (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545-15550.

Subramanian, A., Kuehn, H., Gould, J., Tamayo, P., Mesirov, J.P. (2007) GSEA-P: A desktop application for Gene Set Enrichment Analysis. Bioinformatics, doi: 10.1093/bioinformatics/btm369.

Examples

data(fasting)
data(pathway)

# pca and pca loading
pca <- prcomp(fasting$X, scale=TRUE)
pca <- pca_loading(pca)

# all detected metabolites
metabolites <- colnames(fasting$X)

# statistically significant negatively correlated metabolites in PC1 loading
SIG <- metabolites[pca$loading$R[,1] < 0 & pca$loading$p.value[,1] < 0.05]
ALL <- metabolites #all detected metabolites

# Set response variable
y <- pca$x[,1]

# preparing dataframe
D <- data.frame(ALL,t(fasting$X)) 		# preparing dataframe

# MSEA by Subramanian et al.
M <- pathway$fasting
P <- msea_sub(M,D,y, maxiter = 10) # iteration was set ato 10 for demonstration