Package 'rsemmed'

Search for nodes by name or semantic type

Description

Search for nodes by name (exact match or using regular expressions) or which match supplied semantic types. Perform anti-matching by setting match = FALSE. Capitalization is ignored.

Usage

find_nodes(obj, pattern = NULL, names = NULL, semtypes = NULL, match = TRUE)

Arguments

obj	Either the SemMed graph or a node set (igraph.vs)
pattern	Regular expression used to find matches in node names
names	Character vector of exact node names
semtypes	Character vector of semantic types
match	If TRUE, return nodes that DO match pattern (default). If FALSE, return nodes that DO NOT match.

Value

A vertex sequence of matching nodes

Examples

data(g_mini)
find_nodes(g_mini, pattern = "cortisol")
find_nodes(g_mini, pattern = "cortisol$")
find_nodes(g_mini, pattern = "stress")
find_nodes(g_mini, pattern = "stress") %>%
    find_nodes(pattern = "disorder", match = FALSE)

find_nodes(g_mini, names = "Serum cortisol")
find_nodes(g_mini, names = "Chronic Stress")

find_nodes(g_mini, semtypes = "dsyn")
find_nodes(g_mini, semtypes = c("dsyn", "fndg"))

## pattern and semtypes are combined via OR:
find_nodes(g_mini, pattern = "cortisol", semtypes = "horm")

## To make an AND query, chain find_nodes sequenctially:
find_nodes(g_mini, pattern = "cortisol") %>%
    find_nodes(semtypes = "horm")

---

Shortest paths between node sets

Description

Find all shortest paths between sets of nodes

Usage

find_paths(graph, from, to, weights = NULL)

Arguments

graph	The SemMed graph
from	A set of source nodes. from should be of class igraph.vs (a vertex sequence) or an integer vector.
to	A set of destination nodes. to should be of class igraph.vs (a vertex sequence) or an integer vector.
weights	A numeric vector of edge weights. If NULL (the default), all edges have the default weight of 1.

Details

find_paths relies on igraph::all_shortest_paths to find all shortest paths between the nodes in from and to. This function searches for undirected paths.

Because the Semantic MEDLINE graph is a multigraph, there may be multiple paths with the same sequence of nodes. This function collapses these into a single node sequence. The display functions (text_path and plot_path) take care of showing the multiple edges leading to repeated paths.

Value

A list of shortest paths. List items correspond to the node(s) given in from.

See Also

make_edge_weights to tailor the shortest path search

Examples

data(g_mini)

node_cortisol <- find_nodes(g_mini, names = "Serum cortisol")
node_stress <- find_nodes(g_mini, names = "Chronic Stress")
find_paths(g_mini, from = node_cortisol, to = node_stress)

---

Example data for the rsemmed package

Description

A dataset containing a very small subset of the full Semantic MEDLINE graph.

Usage

data(g_mini)

Format

An igraph with 7 nodes and 15 edges

---

Example data for the rsemmed package

Description

A dataset containing a small subset of the full Semantic MEDLINE graph.

Usage

data(g_small)

Format

An igraph with 1038 nodes and 318,105 edges

---

Get information about edges

Description

Search for nodes by name using regular expressions or which match given semantic types. Perform anti-matching by setting match = FALSE.

Usage

get_edge_features(
    graph,
    include_degree = FALSE,
    include_node_ids = FALSE,
    include_num_instances = FALSE
)

Arguments

graph	The SemMed graph
include_degree	If TRUE, include information on head/tail node degrees.
include_node_ids	If TRUE, include the ID numbers of head/tail nodes.
include_num_instances	If TRUE, include information on the number of times a predication was observed in the Semantic MEDLINE database.

Value

A tbl where each row corresponds to an edge in the Semantic MEDLINE graph. The ordering of the rows corresponds to E(graph). Features (columns) always returned include the name and semantic type of the head (subject) and tail (object) nodes.

See Also

make_edge_weights for using this data to construct edge weights

Examples

data(g_mini)

e_feat <- get_edge_features(g_mini)

---

Obtain the middle nodes of a path

Description

For each pair of source and target nodes in object, obtain the names of middle nodes on paths.

Usage

get_middle_nodes(graph, object, collapse = TRUE)

Arguments

graph	The SemMed graph
object	A vertex sequence (igraph.vs), a list of vertex sequences, or a list of vertex sequence lists
collapse	If TRUE, middle node names for different source-target pairs are combined into one character vector.

Value

A tbl where each row corresponds to a source-target pair in object. The last column is a list-column containing character vectors of names of middle nodes.

Examples

data(g_mini)

node_cortisol <- find_nodes(g_mini, "Serum cortisol")
node_stress <- find_nodes(g_mini, "Chronic Stress")
paths <- find_paths(g_mini, from = node_cortisol, to = node_stress)
middle <- get_middle_nodes(g_mini, paths)

---

Obtain immediate neighbors

Description

Grow a set of nodes into its first order neighborhood.

Usage

grow_nodes(graph, nodes)

Arguments

graph	The SemMed graph
nodes	A vertex sequence (igraph.vs) of nodes to be grown

Details

grow_nodes obtains the set of immediate neighbors of the supplied nodes using igraph::ego. Unlike ego, grow_nodes flattens the result from a list to an ordinary vertex sequence and removes the original search nodes.

Value

A vertex sequence of nodes in the neighborhood (not including the original nodes)

See Also

find_nodes for filtering out irrelevant nodes from this set.

Examples

data(g_mini)

node_cortisol <- find_nodes(g_mini, name = "hypercortisolemia")
nbrs <- grow_nodes(g_mini, node_cortisol)

---

Create edge weights

Description

Create edge weights to modify the shortest path search (find_paths). Discourage and/or encourage certain types of paths by supplying _out and _in arguments, respectively. Node semantic types, node names, and edge predicates are the features that can influence the edge weights. Capitalization is ignored.

Usage

make_edge_weights(
    graph,
    e_feat,
    node_semtypes_out = NULL,
    node_names_out = NULL,
    edge_preds_out = NULL,
    node_semtypes_in = NULL,
    node_names_in = NULL,
    edge_preds_in = NULL
)

Arguments

graph	The SemMed graph
e_feat	A data.frame of edge features from get_edge_features.
node_semtypes_out	A character vector of semantic types to exclude from shortest paths.
node_names_out	A character vector of exact node names to exclude.
edge_preds_out	A character vector of edge predicates to exclude.
node_semtypes_in	A character vector of semantic types to include/encourage in shortest paths.
node_names_in	A character vector of exact node names to include.
edge_preds_in	A character vector of edge predicates to include.

Value

A numeric vector of weights

See Also

find_paths, get_middle_nodes for a way to obtain node names to remove

Examples

data(g_mini)

node_cortisol <- find_nodes(g_mini, names = "Serum cortisol")
node_stress <- find_nodes(g_mini, names = "Chronic Stress")
paths <- find_paths(g_mini, from = node_cortisol, to = node_stress)

e_feat <- get_edge_features(g_mini)

w1 <- make_edge_weights(g_mini, e_feat, edge_preds_in = "COEXISTS_WITH")
paths1 <- find_paths(g_mini,
    from = node_cortisol, to = node_stress, weights = w1)

w2 <- make_edge_weights(g_mini, e_feat, edge_preds_in = "ISA",
                        node_names_out = "Stress")
paths2 <- find_paths(g_mini,
    from = node_cortisol, to = node_stress, weights = w2)

---

Display path (plot form)

Description

Plot the graph form of a path

Usage

plot_path(graph, path)

Arguments

graph	The SemMed graph
path	A vertex sequence (igraph.vs) (the path to display)

Details

All connections among nodes along the supplied path are plotted with nodes labeled with their name and edges labeled with their predicate.

Value

A plot is created on the current graphics device

See Also

text_path for textual display of paths

Examples

data(g_mini)

node_cortisol <- find_nodes(g_mini, names = "Serum cortisol")
node_stress <- find_nodes(g_mini, names = "Chronic Stress")
paths <- find_paths(g_mini, from = node_cortisol, to = node_stress)
plot_path(g_mini, paths[[1]][[1]])

---

Summarize predicates

Description

Summarize the predicates present in a collection of paths

Usage

summarize_predicates(graph, object, print = TRUE)

Arguments

graph	The SemMed graph
object	A vertex sequence (igraph.vs), a list of vertex sequences, or a list of vertex sequence lists
print	If TRUE, information on predicates will be printed to the screen.

Details

Because predicates are edge features, it is assumed that by using summarize_predicates the nodes contained in object are ordered (paths). This is why summarize_semtypes has the is_path argument, but summarize_predicates does not. summarize_predicates tabulates edge predicates across paths corresponding to each from-to pair in object.

Value

A tbl where each row corresponds to a from-to pair in object. The last column is a list-column containing table's of predicate counts.

See Also

summarize_semtypes for tabulating semantic types of nodes in paths or other node collections

Examples

data(g_mini)

node_cortisol <- find_nodes(g_mini, "Serum cortisol")
node_stress <- find_nodes(g_mini, "Chronic Stress")
paths <- find_paths(g_mini, from = node_cortisol, to = node_stress)
summarize_predicates(g_mini, paths)

---

Summarize semantic types

Description

Summarize the semantic types present in a collection of nodes

Usage

summarize_semtypes(graph, object, print = TRUE, is_path = TRUE)

Arguments

graph	The SemMed graph
object	A vertex sequence (igraph.vs), a list of vertex sequences, or a list of vertex sequence lists
print	If TRUE, information on semantic types will be printed to the screen.
is_path	If TRUE, object contains paths (ordered sequences of nodes).

Details

summarize_semtypes summarizes the semantic types present in supplied node collections and has different behavior depending on whether the node collection is ordered (paths) or unordered. Using is_path = TRUE indicates that the nodes are ordered. Using is_path = FALSE indicates that the nodes are an unordered collection, often from find_nodes or grow_nodes.

Using is_path = TRUE: When the node collection is ordered, the object is assumed to be the result of find_paths or a subset of such an object. Because find_paths returns a list of paths lists, summarize_semtypes takes a single path, a list of paths, or a list of path lists as input. In the case of a collection of ordered nodes, summarize_semtypes counts the semantic types present in object. If a node is associated with multiple semantic types, each type is counted once. The first and last nodes of each path are removed they correspond to the nodes in from and to from find_paths, and it is assumed that the middle nodes on the paths are more of interest. The tabulations are printed to screen (if print = TRUE) and returned as table's. These table's are bundled into a list-column of a tbl in the (invisbly returned) output. Each row of the tbl corresponds to a from-to pair present in object.

Using is_path = FALSE: This option is for summarizing results from find_nodes and grow_nodes, which return unordered node sets. (Note: paths and unordered node sets are both represented as igraph vertex sequences (class igraph.vs).) The printed output shows information for each semantic type present in object. It shows all nodes of that semantic type as well as their degree and degree percentile within the entire graph. The (invisibly returned) output combines all of the printed information in a tbl.

Value

Output is returned invisibly. If is_path = TRUE, a tbl where each row corresponds to a from-to pair in object. The last column is a list-column containing table's of semantic type counts. If is_path = FALSE, a tbl where each row corresponds to a name-semantic type combination. Columns give node name, semantic type, degree, and degree percentile.

See Also

summarize_predicates for summarizing predicates on edges

find_paths for searching for paths between node sets

find_nodes and grow_nodes for searching for and filtering nodes

Examples

data(g_mini)

node_cortisol <- find_nodes(g_mini, "Serum cortisol")
node_stress <- find_nodes(g_mini, "Chronic Stress")
paths <- find_paths(g_mini, from = node_cortisol, to = node_stress)
summarize_semtypes(g_mini, paths)

nodes_mood <- find_nodes(g_mini, "mood")
summarize_semtypes(g_mini, nodes_mood, is_path = FALSE)

---

Display path (text form)

Description

Show a text display of a path and obtain output that can be used to explore predications along the path. (A predication is a SUBJECT–LINKING VERB–>OBJECT triple.)

Usage

text_path(graph, path, print = TRUE)

Arguments

graph	The SemMed graph
path	A vertex sequence (igraph.vs) (the path to display)
print	Print the path to screen?

Details

text_path invisibly returns a list of tbl's containing information on the predications on the path. Each list element is a tbl that corresponds to a (sequential) pair of nodes along the path. The tbl contains information on the subject and object node's name and semantic type as well as all predicates linking the subject and object.

Value

Invisibly returns a list of predications for each pair of nodes along the path.

See Also

plot_path for plotting paths

Examples

data(g_mini)

node_cortisol <- find_nodes(g_mini, names = "Serum cortisol")
node_stress <- find_nodes(g_mini, names = "Chronic Stress")
paths <- find_paths(g_mini, from = node_cortisol, to = node_stress)
text_path(g_mini, paths[[1]][[1]])
result <- text_path(g_mini, paths[[1]][[1]], print = FALSE)

---