interactions_result {famat} | 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.

[Package famat version 1.0.0 Index]