interactions_result: Output of 'interactions' function
In emiliesecherre/famat: Functional analysis of metabolic and transcriptomic data

interactions_result

R Documentation

Output of `interactions` function

Description

List containing informations about interactions between genes and metabolites, centrality and pathways. Direct interactions extraction was performed using BioPax, KGML and GPML files parsed with PaxtoolsR, graphite and author's parsers.

Usage

data("interactions_result")

Format

List of 8 items.

size

Description on which elements (from user's list or not) are contained in pathways from pathway enrichment analysis. A data frame with 286 rows and 9 variables.

path: Pathways obtained throught pathways enrichment analysis on KEgg, Reactome and Wikipathways pathways.
nb_gene_query: Number of user's genes contained in the pathway (0–2).
gene_que: User's genes contained in the pathway (ACAA1, SLC6A12, ACAA1 # SLC6A12).
nb_gene_tot: Total number of genes contained in the pathway (0–2075).
genes: All the genes contained in the pathway.
nb_meta_query: Number of user's metabolites contained in the pathway (0–2).
meta_que: User's metabolites contained in the pathway (Betaine, ATP, Betaine # ATP, ATP # Betaine).
nb_meta_tot: Total number of metabolites contained in the pathway (0–915).
meta: All the metabolites contained in the pathway.

pathtot

All results of pathways enrichment analysis performed on Kegg, Reactome and Wikipathways pathways. A data frame with 286 rows and 2 variables.

name: Name of pathways resulting in genes pathway enrichment analysis performed on Kegg, Reactome and Wikipathways.
id: Identifiers of pathways resulting in genes pathway enrichment analysis performed on Kegg, Reactome and Wikipathways.

tagged

Description of all direct interactions between user's elements in pathways. A data frame with 11 rows and 6 variables.

from: First element of the direct interaction (Betaine, SLC6A12)
link: Description of how the two elements interact (Control(In: ACTIVATION of BiochemicalReaction), controls-transport-of-chemical).
to: Second element of the direct interaction (Betaine, SLC6A12)
path: Pathway containing the direct interaction (R-HSA-112310, R-HSA-112315, R-HSA-112316, R-HSA-382551, R-HSA-425366, R-HSA-425393, R-HSA-425407, R-HSA-888590, R-HSA-352230, R-HSA-442660, R-HSA-888593)
tag: Summary of elements concerned by the interaction (Betaine / SLC6A12, SLC6A12 / Betaine)
type: Interaction type, can be gene/gene, metabolite/metabolite, or gene/metabolite (g/m)

keggchebiname

Dataframe containing all human metabolites ids (kegg and chebi) and names. A data frame with 16075 rows and 3 variables.

kegg: Kegg_compound identifiers of all human metabolites.
chebi: Chebi identifiers of all human metabolites.
name: Names of all human metabolites.

central

List of pathways, each pathway containing the number of direct interactions between an element of user's list and other elements in the pathway. A list of 138 items.

no_path

Dataframe containing direct interactions between elements from the user's list, but not per pathways. A data frame with 1 rows and 6 variables.

from: First element of the direct interaction (Betaine, SLC6A12)
link: Description of how the two elements interact (Control(In: ACTIVATION of BiochemicalReaction), controls-transport-of-chemical).
to: Second element of the direct interaction (Betaine, SLC6A12)
path: Pathways containing the direct interaction ("R-HSA-112310, R-HSA-112315, R-HSA-112316, R-HSA-382551, R-HSA-425366, R-HSA-425393, R-HSA-425407, R-HSA-888590, R-HSA-352230, R-HSA-442660, R-HSA-888593")
tag: Summary of elements concerned by the interaction (Betaine / SLC6A12)
type: Interaction type, can be gene/gene, metabolite/metabolite, or gene/metabolite (g/m)

genes

Vector containing user's genes (ACAA1, SLC6A12)

meta

Vector containing user's metabolites (C00002, C00719)

Source

interactions function.

References

Luna, A., Babur, O., Aksoy, A. B, Demir, E., Sander, C. (2015).“PaxtoolsR: Pathway Analysis in R Using Pathway Commons.” Bioinformatics.

Sales G, Calura E, Cavalieri D, Romualdi C (2012). “graphite - a Bioconductor package to convert pathway topology to gene network.” BMC Bioinformatics. https://bmcbioinformatics.biomedcentral.com/articles/10 . 1186/1471-2105-13-20.

emiliesecherre/famat documentation built on April 23, 2023, 9:15 p.m.