rbioapi (version 0.8.2)

rba_string_interactions_network: Get STRING Network Interactions

Description

This function will retrieve Sting interaction pairs among your input protein ids, with the combined score and separate score for each STRING score channels. You can further expand your network to a defined size by providing "add_node" parameter.

Usage

rba_string_interactions_network(
  ids,
  species = NULL,
  required_score = NULL,
  add_nodes = NULL,
  network_type = "functional",
  use_query_labels = FALSE,
  ...
)

Value

A data frame which each row is a network interaction and the columns contains interactor information and interaction scores:

• stringId_A: STRING identifier (protein A)

• stringId_B:STRING identifier (protein B)

• preferredName_A: common protein name (protein A)

• preferredName_B: common protein name (protein B)

• ncbiTaxonId: NCBI taxon identifier

• score: combined score

• nscore: gene neighborhood score

• fscore: gene fusion score

• pscore: phylogenetic profile score

• ascore: co-expression score

• escore: experimental score

• dscore: database score

• tscore: textmining score

Arguments

ids

Your protein IDs. It is strongly recommended to supply STRING IDs. See rba_string_map_ids for more information.

species

Numeric: NCBI Taxonomy identifier; Human Taxonomy ID is 9606. (Recommended, but optional if your input is less than 100 IDs.)

required_score

Numeric: A minimum of interaction score for an interaction to be included in the image. if not supplied, the threshold will be applied by STRING Based in the network. (low Confidence = 150, Medium Confidence = 400, High Confidence = 700, Highest confidence = 900)

add_nodes

Numeric: Number of neighboring proteins to be added to the network. If none supplied by the user, this argument value will depend on the number of supplied "ids" argument:

1. Single id: add_node will be set to 10 to retrieve the interaction neighborhood of you input protein.

2. Multiple ids: add_node will be set to 0, thus the output will be the interactions between your input proteins.

network_type

should be one of:

• "functional": (default) The edge's indicate both physical and functional associations.

• "physical": The edges indicate that two proteins have a physical interaction or are parts of a complex.

use_query_labels

Logical: (Default = FALSE) Use the names supplied with the 'ids' argument as the nodes labels instead of STRING's default ones.

...

rbioapi option(s). See rba_options's arguments manual for more information on available options.

Corresponding API Resources

"POST https://string-db.org/api/{output-format}/network?identifiers= {your_identifiers}&{optional_parameters}"

Details

Note that this function will return interactions between your set of supplied proteins, or at most, expand the interaction network by the given parameters. TO retrieve a list of all possible interacting proteins with your given input, see rba_string_interaction_partners.

References

• Damian Szklarczyk, Rebecca Kirsch, Mikaela Koutrouli, Katerina Nastou, Farrokh Mehryary, Radja Hachilif, Annika L Gable, Tao Fang, Nadezhda T Doncheva, Sampo Pyysalo, Peer Bork, Lars J Jensen, Christian von Mering, The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest, Nucleic Acids Research, Volume 51, Issue D1, 6 January 2023, Pages D638–D646, https://doi.org/10.1093/nar/gkac1000

• STRING API Documentation

• Citations note on STRING website

See Also

rba_string_map_ids, rba_string_interaction_partners

Other "STRING": rba_string_annotations(), rba_string_enrichment(), rba_string_enrichment_image(), rba_string_enrichment_ppi(), rba_string_homology_inter(), rba_string_homology_intra(), rba_string_interaction_partners(), rba_string_map_ids(), rba_string_network_image(), rba_string_version()

Examples

# \donttest{
rba_string_interactions_network(ids = c("9606.ENSP00000269305",
    "9606.ENSP00000398698",
    "9606.ENSP00000275493"),
    network_type = "functional")
# }
# \donttest{
rba_string_interactions_network(ids = c("9606.ENSP00000269305",
    "9606.ENSP00000398698",
    "9606.ENSP00000275493"),
    species = 9606,
    add_nodes = 10)
# }