Remove evidence curated as incorrect

Subtracts the evidence curated as incorrect, from get_curations(), from each edge's evidence_count, then drops the edges left below min_evidence, and the nodes those edges leave without any edge. Edges left with no evidence are dropped whatever min_evidence is. A message says how many edges were dropped.

Usage

filter_by_curation(network, min_evidence = 1, backend = NULL)

Arguments

network

list of nodes and edges from get_network(). edges needs the columns source, target, statement_id, and evidence_count, and backend_database unless backend is given.

min_evidence

minimum evidence count per edge, after subtracting the incorrect evidence

backend

the backend to get the curations from, e.g. indra_backend(). NULL (default) uses the default backend named in each edge's backend_database. Pass a backend to use one built with non-default settings, such as indra_backend(curation_url = ). A backend without curations, such as one with no get_curations() method, gives an error naming it.

Value

network, with edges$evidence_count reduced and the dropped edges and nodes removed. Other elements of network are kept.

Details

Run it after any filter that pools edges, such as the PTM-site filter of getSubnetworkFromIndra(): dropping edges first can change which edges such a filter keeps.

See also

get_curations()

Examples

# \donttest{
input <- data.table::fread(system.file(
    "extdata/groupComparisonModel.csv",
    package = "MSstatsBioNet"
))
indra <- indra_backend()
entities <- prepare_entities(input, entity_type = "protein",
                             id_type = "uniprot")
entities <- convert_ids(indra, entities)
entities <- select_entities(entities, pvalue_cutoff = 0.05)
network <- get_network(indra, entities, interaction_types = "Complex")
#> INDRA subnetwork: how are 10 selected proteins connected to each other, with no other nodes added?
network <- filter_by_curation(network, min_evidence = 2)
#> Dropping 12 edge(s) with fewer than 2 evidence after removing the evidence curated as incorrect.
head(network$edges)
#>    source target interaction directed site confidence evidence_count
#> 4  P05067 O60313     Complex    FALSE <NA>  0.6896123             23
#> 6  P05067 P05362     Complex    FALSE <NA>  0.6549329             13
#> 7  O60313 P05067     Complex    FALSE <NA>  0.6896123             23
#> 9  O00217 O75306     Complex    FALSE <NA>  0.7981153              3
#> 12 O00217 P08574     Complex    FALSE <NA>  0.8216256              3
#> 14 P05362 P05067     Complex    FALSE <NA>  0.6549329             13
#>                                                                evidence_url
#> 4  https://db.indra.bio/statements/from_hash/-12253697417005038?format=html
#> 6  https://db.indra.bio/statements/from_hash/-20220236678417803?format=html
#> 7  https://db.indra.bio/statements/from_hash/-12253697417005038?format=html
#> 9   https://db.indra.bio/statements/from_hash/35453498871697150?format=html
#> 12 https://db.indra.bio/statements/from_hash/-15796466026283356?format=html
#> 14 https://db.indra.bio/statements/from_hash/-20220236678417803?format=html
#>          statement_id backend_database query_type              evidence_sources
#> 4  -12253697417005038            INDRA subnetwork {"sparser": 21, "biogrid": 2}
#> 6  -20220236678417803            INDRA subnetwork   {"sparser": 10, "reach": 3}
#> 7  -12253697417005038            INDRA subnetwork {"sparser": 21, "biogrid": 2}
#> 9   35453498871697150            INDRA subnetwork                {"biogrid": 3}
#> 12 -15796466026283356            INDRA subnetwork                {"biogrid": 3}
#> 14 -20220236678417803            INDRA subnetwork   {"sparser": 10, "reach": 3}
#>    paperCount
#> 4           1
#> 6           1
#> 7           1
#> 9           1
#> 12          1
#> 14          1
# }