path_enrich: Pathway enrichment analysis

In famat: Functional analysis of metabolic and transcriptomic data

Description

Perform a pathway enrichment analysis using a list of genes and a list of metabolites. Pathways enrichment analysis is performed using MPINet for metabolites and gprofiler2 for genes.

Usage

    path_enrich(source, metabo, genes)

Arguments

source	Pathways database used, either Kegg ("KEGG"), Reactome ("REAC") or Wikipathays ("WP")
metabo	Dataframe with three columns : the first column contain the list of metabolites, the second some quantitative data about the metabolites, the last one words "DOWN" or "UP" depending on the metabolites concentration behavior in a certain condition. Last two columns can contain only/some NAs. All metabolites ids are KEGG Compound ids.
genes	Dataframe with three columns : the first column contain the list of genes, the second some quantitative data about the genes, the last one words "DOWN" or "UP" depending on the genes expression behavior in a certain condition. Last two columns can contain only/some NAs. All genes ids are gene symbol.

Value

A list containing :

resmeta	Results of metabolites pathway enrichment analysis
resgene	Results of genes pathway enrichment analysis
genes	Vector containing genes
metabo	Vector containing metabolites

This list is used by interactions function.

Author(s)

Emilie Secherre [e-mail]

References

Yanjun Xu, Chunquan Li and Xia Li (2013). MPINet: The package can implement the network-based metabolite pathway identification of pathways.. R package version 1.0. https://CRAN.R-project.org/package=MPINet

Liis Kolberg and Uku Raudvere (2020). gprofiler2: Interface to the 'g:Profiler' Toolset. R package version 0.2.0. https://CRAN.R-project.org/package=gprofiler2

See Also

interactions

Examples

    ## load example data
    data(genes)
    data(meta)

    ## perform pathway enrichment analysis on Reactome pathways
    listr=path_enrich("REAC", meta, genes)

famat documentation built on Nov. 8, 2020, 5:56 p.m.