Validate a network against the edge and node contract — validate

Checks that a network returned by getSubnetworkFromIndra, or built by hand from another source, has the columns, types, and vocabularies that the visualization and filtering functions rely on.

Usage

validate_network(network)

Arguments

network: list with nodes and edges data.frames.

Value

network, invisibly. Stops with an error listing every problem found.

Details

Required edge columns: source, target (both matching nodes$id), interaction (an INDRA statement type such as "Activation" or "Complex"), directed (logical), site (PTM site on the target such as "S148", ;-joined when there are several, or NA), confidence (in [0, 1], or NA when the source provides no score), evidence_count (whole number, at least 1, not NA), evidence_url, statement_id (character), backend_database, and query_type. Edges of the symmetric statement types "Complex" and "Association" must have directed = FALSE. Several edges can share a statement_id: an undirected statement can be listed in both directions, and a statement reaches every node with its grounding (see get_network()).

Required node columns: id, entity_type (e.g. "protein", "ptm_site", "metabolite", "family"), entity_name, namespace and entity_id (the grounding, NA when unknown), measured (logical: the node is in the input data), included_in_query (logical: the node was part of the query), and node_role (why the node is in the network, e.g. "passed_cutoffs" or "user_added", or several joined by ";" after merge_networks()). An id can repeat, once per PTM site row of the same protein. When present, site, has_measured_sites, logFC, and adj.pvalue are type-checked. Nodes with measured == FALSE must have NA statistics.

Confidence values are comparable within one backend_database, not across sources.

Examples

network <- list(
    nodes = data.frame(
        id = c("CHK1_HUMAN", "CDC25A_HUMAN"),
        entity_type = "protein",
        entity_name = c("CHEK1", "CDC25A"),
        namespace = "HGNC",
        entity_id = c("1925", "1725"),
        measured = TRUE,
        included_in_query = TRUE,
        node_role = "passed_cutoffs"
    ),
    edges = data.frame(
        source = "CHK1_HUMAN",
        target = "CDC25A_HUMAN",
        interaction = "Phosphorylation",
        directed = TRUE,
        site = "S76",
        confidence = 0.99,
        evidence_count = 12L,
        evidence_url = paste0("https://db.indra.bio/statements/",
                                "from_hash/-1234?format=html"),
        statement_id = "-1234",
        backend_database = "INDRA",
        query_type = "subnetwork"
    )
)
validate_network(network)