Package 'graphite' reference manual

Title:	GRAPH Interaction from pathway Topological Environment
Description:	Graph objects from pathway topology derived from KEGG, Panther, PathBank, PharmGKB, Reactome SMPDB and WikiPathways databases.
Authors:	Gabriele Sales [cre], Enrica Calura [aut], Chiara Romualdi [aut]
Maintainer:	Gabriele Sales <[email protected]>
License:	AGPL-3
Version:	1.51.0
Built:	2024-06-30 02:30:11 UTC
Source:	https://github.com/bioc/graphite

Convertion of PathwayLists into lists.

Description

Converts a PathwayList into a list of Pathways.

Usage

  ## S3 method for class 'PathwayList'
as.list(x, ...)
## S3 method for class 'PathwayList'
as.list(x, ...)

Arguments

`x`	a `PathwayList` object
`...`	extra arguments to as.list

Value

A list of pathways.

Author(s)

Gabriele Sales

Examples

  as.list(pathways("hsapiens", "kegg"))
as.list(pathways("hsapiens", "kegg"))

Build a Pathway object.

Description

This function creates a new object of type Pathway given a data frame describing its edges.

Usage

buildPathway(id, title, species, database, proteinEdges,
             metaboliteEdges = NULL, mixedEdges = NULL,
             timestamp = NULL)
buildPathway(id, title, species, database, proteinEdges,
             metaboliteEdges = NULL, mixedEdges = NULL,
             timestamp = NULL)

Arguments

`id`	the pathway identifier.
`title`	the title of the pathway.
`species`	the species the pathway belongs to.
`database`	the name of the database the pathway derives from.
`proteinEdges`	a data.frame of edges between proteins (or genes). Must have the following columns: src_type, src, dest_type, dest, direction and type. Direction must be one of the two strings: "directed" or "undirected".
`metaboliteEdges`	interactions between metabolites. Can be `NULL`. Otherwise, it must have the same structure as `proteinEdges`.
`mixedEdges`	interactions between metabolites and proteins. Can be `NULL`. Otherwise, it must have the same structure as `proteinEdges`.
`timestamp`	when the pathway was annotated, by default the time `buildPathway` is called.

Value

A new Pathway instance.

Examples

edges <- data.frame(src_type = "ENTREZID", src="672",
                    dest_type = "ENTREZID", dest="7157",
                    direction="undirected", type="binding")
pathway <- buildPathway("#1", "example", "hsapiens", "database", edges)

# Example with metabolites:
edges <- data.frame(src_type = "ENTREZID", src="672",
                    dest_type = "ENTREZID", dest="7157",
                    direction="undirected", type="binding")
mixed <- data.frame(src_type = "CHEBI", src="77750",
                    dest_type = "ENTREZID", dest="7157",
                    direction="undirected", type="binding")
pathway <- buildPathway("#1", "example", "hsapiens", "database",
                        edges, mixedEdges = mixed)
edges <- data.frame(src_type = "ENTREZID", src="672",
                    dest_type = "ENTREZID", dest="7157",
                    direction="undirected", type="binding")
pathway <- buildPathway("#1", "example", "hsapiens", "database", edges)

# Example with metabolites:
edges <- data.frame(src_type = "ENTREZID", src="672",
                    dest_type = "ENTREZID", dest="7157",
                    direction="undirected", type="binding")
mixed <- data.frame(src_type = "CHEBI", src="77750",
                    dest_type = "ENTREZID", dest="7157",
                    direction="undirected", type="binding")
pathway <- buildPathway("#1", "example", "hsapiens", "database",
                        edges, mixedEdges = mixed)

Convert the node identifiers of a pathway.

Description

Converts the node identifiers of pathways.

If the option Ncpus is set to a value larger than 1 and the package parallel is installed, the conversion procedure will automatically use multiple cores.

Usage

convertIdentifiers(x, to)
convertIdentifiers(x, to)

Arguments

`x`	can be a list of pathways or a single pathway
`to`	a string describing the type of the identifier. Can assume the values `"entrez"`, `"symbol"` or the name of one of the columns provided by an Annotation package (for example, `"UNIPROT"`).

Value

A Pathway object.

Examples

  r <- pathways("hsapiens", "reactome")
  convertIdentifiers(r$`mTORC1-mediated signalling`, "symbol")
r <- pathways("hsapiens", "reactome")
  convertIdentifiers(r$`mTORC1-mediated signalling`, "symbol")

Plot a pathway graph in Cytoscape

Description

Renders the topology of a pathway as a Cytoscape graph.

Usage

cytoscapePlot(pathway, ..., cy.ver = 3)
cytoscapePlot(pathway, ..., cy.ver = 3)

Arguments

`pathway`	a `Pathway` object.
`...`	optional arguments forwarded to `pathwayGraph`.
`cy.ver`	select a Cytoscape version. Only version 3 is supported in this release.

Details

Requires the RCy3 package.

Value

An invisible list with two items:

`graph`	the `graphNEL` object sent to Cytoscape.
`suid`	the RCy3 network SUID.

Examples

## Not run: 
  r <- pathways()
  cytoscapePlot(convertIdentifiers(reactome$`Unwinding of DNA`, "symbol"))

## End(Not run)
## Not run: 
  r <- pathways()
  cytoscapePlot(convertIdentifiers(reactome$`Unwinding of DNA`, "symbol"))

## End(Not run)

Class `"Pathway"`

Description

A biological pathway.

Variants

A Pathway instance actually stores multiple variants of the same biological data.

This is the list of included variants:

proteins: includes only interactions among proteins;
metabolites: includes only interactions among metabolites;
mixed: includes all available interactions.

Methods

pathwayId(p):

Returns the native ID of the pathway.

pathwayTitle(p):

Returns the title of the pathway.

pathwayDatabase(p):

Returns the name of the database the pathway was derived from.

pathwaySpecies(p):

Returns the name of the species in which the pathway was annotated.

pathwayTimestamp(p):

Returns the date of pathway data retrieval.

pathwayURL(p):

Returns the URL of the pathway in its original database, if available.

convertIdentifiers(p, to):

Returns a new pathway using a different type of node identifiers.

edges(p, which = c("proteins", "metabolites", "mixed"), stringsAsFactors = TRUE):

Returns a data.frame describing the edges of this pathway.

The option which selects the desired pathway variant (see section "Variants" above).

If stringsAsFactors is TRUE, strings are converted to factors.

nodes(p, which = c("proteins", "metabolites", "mixed")):

Returns the names of the nodes belonging to this pathway.

The option which selects the desired pathway variant (see section "Variants" above).

plot(p):

Shows the pathway topology in Cytoscape.

runClipper(p, expr, classes, method, ...):

Runs a clipper analysis over the pathway.

runTopologyGSA(p, test, exp1, exp2, alpha, ...):

Runs a topologyGSA analysis over the pathway.

Author(s)

Gabriele Sales

Examples

  reactome <- pathways("hsapiens", "reactome")
  pathway <- reactome[[1]]

  pathwayTitle(pathway)
  pathwaySpecies(pathway)
  nodes(pathway)
  edges(pathway)
reactome <- pathways("hsapiens", "reactome")
  pathway <- reactome[[1]]

  pathwayTitle(pathway)
  pathwaySpecies(pathway)
  nodes(pathway)
  edges(pathway)

List the available pathway databases.

Description

Obtains the list of pathway databases available through graphite.

Usage

  pathwayDatabases()
pathwayDatabases()

Value

Returns a data.frame with two columns: species and database.

Author(s)

Gabriele Sales

Examples

  pathwayDatabases()
pathwayDatabases()

Graph representing the topology of a pathway

Description

Builds a graphNEL object representing the topology of a pathway.

Usage

  pathwayGraph(pathway, which = "proteins", edge.types = NULL)
pathwayGraph(pathway, which = "proteins", edge.types = NULL)

Arguments

pathway

a Pathway object.

which

the pathway variant you want.

See Pathway documentation for a list of the supported variants.

edge.types

keep only the edges maching the type names in this vector.

Value

A graphNEL object.

Examples

  r <- pathways("hsapiens", "reactome")
  pathwayGraph(r$`mTORC1-mediated signalling`, edge.types="Binding")
r <- pathways("hsapiens", "reactome")
  pathwayGraph(r$`mTORC1-mediated signalling`, edge.types="Binding")

Class `"PathwayList"`

Description

A collection of pathways from a single database.

Extends

Class "Pathways", directly.

Methods

l[i]: returns a selection of the pathways contained in the pathway list.
l[[i]]: gives access to one of the pathways contained in the pathway list.
l$`title`: loads a pathways by its title.
convertIdentifiers(l, to): returns a new list of pathways using a different type of node identifiers.
length(l): returns the number of pathways contained in the list.
names(l): returns the titles of the pathways contained in the list.
prepareSPIA(l, pathwaySetName, print.names=FALSE): prepares the pathways for a SPIA analysis.
runClipper(l, expr, classes, method, maxNodes=150, ...): runs a clipper analysis over all the pathways in the list.
runTopologyGSA(l, test, exp1, exp2, alpha, maxNodes=150, ...): runs a topologyGSA analysis over all the pathways in the list.

Author(s)

Gabriele Sales

Retrieve a list of pathways.

Description

Retrieve a list of pathways from a database for a given species.

graphite currently supports the following databases:

Call the pathwayDatabase function for more details.

Usage

  pathways(species, database)
pathways(species, database)

Arguments

`species`	one of the supported species
`database`	the name of the pathway database

Value

A PathwayList object.

Examples

  pathways("hsapiens", "reactome")
pathways("hsapiens", "reactome")

Class `"Pathways"`

Description

A virtual class acting as a common parent to all other classes representing pathway databases.

Objects from the Class

A virtual Class: No objects may be created from it.

Methods

No methods defined with class "Pathways" in the signature.

Author(s)

Gabriele Sales

Prepare pathway dataset needed by runSPIA.

Description

Prepare pathway dataset needed by runSPIA. See runSPIA and spia for more details.

Usage

  prepareSPIA(db, pathwaySetName, print.names = FALSE)
prepareSPIA(db, pathwaySetName, print.names = FALSE)

Arguments

`db`	a `PathwayList` object or a list of `Pathway`s.
`pathwaySetName`	name of the output pathway set.
`print.names`	print pathway names as the conversion advances.

Value

This function has no return value.

References

Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim JS, Kim CJ, Kusanovic JP, Romero R. A novel signaling pathway impact analysis. Bioinformatics. 2009 Jan 1;25(1):75-82.

Adi L. Tarca, Sorin Draghici, Purvesh Khatri, et. al, A Signaling Pathway Impact Analysis for Microarray Experiments, 2008, Bioinformatics, 2009, 25(1):75-82.

Draghici, S., Khatri, P., Tarca, A.L., Amin, K., Done, A., Voichita, C., Georgescu, C., Romero, R.: A systems biology approach for pathway level analysis. Genome Research, 17, 2007.

Run SPIA analysis

Description

Run a topological analysis on an expression dataset using SPIA.

Usage

  runSPIA(de, all, pathwaySetName, ...)
runSPIA(de, all, pathwaySetName, ...)

Arguments

`de`	A named vector containing log2 fold-changes of the differentially expressed genes. The names of this numeric vector are Entrez gene IDs.
`all`	A vector with the Entrez IDs in the reference set. If the data was obtained from a microarray experiment, this set will contain all genes present on the specific array used for the experiment. This vector should contain all names of the 'de' argument.
`pathwaySetName`	The name of a pathway set created with `prepareSPIA`.
`...`	Additional options to pass to `spia`.

Details

The spia option "organism" is internally used. It is an error use it in the additional options.

Value

The same of spia, without KEGG links. A data frame containing the ranked pathways and various statistics: pSize is the number of genes on the pathway; NDE is the number of DE genes per pathway; tA is the observed total preturbation accumulation in the pathway; pNDE is the probability to observe at least NDE genes on the pathway using a hypergeometric model; pPERT is the probability to observe a total accumulation more extreme than tA only by chance; pG is the p-value obtained by combining pNDE and pPERT; pGFdr and pGFWER are the False Discovery Rate and respectively Bonferroni adjusted global p-values; and the Status gives the direction in which the pathway is perturbed (activated or inhibited).

References

Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim JS, Kim CJ, Kusanovic JP, Romero R. A novel signaling pathway impact analysis. Bioinformatics. 2009 Jan 1;25(1):75-82.

Adi L. Tarca, Sorin Draghici, Purvesh Khatri, et. al, A Signaling Pathway Impact Analysis for Microarray Experiments, 2008, Bioinformatics, 2009, 25(1):75-82.

Draghici, S., Khatri, P., Tarca, A.L., Amin, K., Done, A., Voichita, C., Georgescu, C., Romero, R.: A systems biology approach for pathway level analysis. Genome Research, 17, 2007.

Examples

if (require(SPIA) && require(hgu133plus2.db)) {
  data(colorectalcancer)

  top$ENTREZ <- mapIds(hgu133plus2.db, top$ID, "ENTREZID", "PROBEID", multiVals = "first")
  top <- top[!is.na(top$ENTREZ) & !duplicated(top$ENTREZ), ]
  top$ENTREZ <- paste("ENTREZID", top$ENTREZ, sep = ":")
  tg1 <- top[top$adj.P.Val < 0.05, ]

  DE_Colorectal = tg1$logFC
  names(DE_Colorectal) <- tg1$ENTREZ
  ALL_Colorectal <- top$ENTREZ

  kegg <- pathways("hsapiens", "kegg")[1:20]
  kegg <- convertIdentifiers(kegg, "ENTREZID")
  prepareSPIA(kegg, "keggEx")
  runSPIA(de = DE_Colorectal, all = ALL_Colorectal, "keggEx")

  unlink("keggExSPIA.RData")
}
if (require(SPIA) && require(hgu133plus2.db)) {
  data(colorectalcancer)

  top$ENTREZ <- mapIds(hgu133plus2.db, top$ID, "ENTREZID", "PROBEID", multiVals = "first")
  top <- top[!is.na(top$ENTREZ) & !duplicated(top$ENTREZ), ]
  top$ENTREZ <- paste("ENTREZID", top$ENTREZ, sep = ":")
  tg1 <- top[top$adj.P.Val < 0.05, ]

  DE_Colorectal = tg1$logFC
  names(DE_Colorectal) <- tg1$ENTREZ
  ALL_Colorectal <- top$ENTREZ

  kegg <- pathways("hsapiens", "kegg")[1:20]
  kegg <- convertIdentifiers(kegg, "ENTREZID")
  prepareSPIA(kegg, "keggEx")
  runSPIA(de = DE_Colorectal, all = ALL_Colorectal, "keggEx")

  unlink("keggExSPIA.RData")
}

Run a topological analysis on an expression dataset using topologyGSA.

Description

Use graphical models to test the pathway components highlighting those involved in its deregulation.

If the option Ncpus is set to a value larger than 1 and the package parallel is installed, the conversion procedure will automatically use multiple cores.

Usage

  runTopologyGSA(x, test, exp1, exp2, alpha, ...)
runTopologyGSA(x, test, exp1, exp2, alpha, ...)

Arguments

`x`	a `PathwayList`, a list of `Pathway`s or a single `Pathway` object.
`test`	Either `"var"` and `"mean"`. Determine the type of test used by topologyGSA.
`exp1`	Experiment matrix of the first class, genes in columns.
`exp2`	Experiment matrix of the second class, genes in columns.
`alpha`	Significance level of the test.
`...`	Additional parameters forwarded to `topologyGSA`. When invoked on a `PathwayList`, can use the named option "maxNodes" to limit the analysis to those pathways having up to this given number of nodes.

Details

This function produces a warning and returns NULL when the number of genes in common between the expression matrices and the pathway is less than 3.

Value

See documentation of pathway.var.test and pathway.mean.test.

References

Massa MS, Chiogna M, Romualdi C. Gene set analysis exploiting the topology of a pathway. BMC System Biol. 2010 Sep 1;4:121.

Examples

if (require(topologyGSA)) {
  data(examples)
  colnames(y1) <- paste("SYMBOL", colnames(y1), sep = ":")
  colnames(y2) <- paste("SYMBOL", colnames(y2), sep = ":")

  k <- pathways("hsapiens", "kegg")
  p <- convertIdentifiers(k[["Fc epsilon RI signaling pathway"]], "SYMBOL")
  runTopologyGSA(p, "var", y1, y2, 0.05)
}
if (require(topologyGSA)) {
  data(examples)
  colnames(y1) <- paste("SYMBOL", colnames(y1), sep = ":")
  colnames(y2) <- paste("SYMBOL", colnames(y2), sep = ":")

  k <- pathways("hsapiens", "kegg")
  p <- convertIdentifiers(k[["Fc epsilon RI signaling pathway"]], "SYMBOL")
  runTopologyGSA(p, "var", y1, y2, 0.05)
}

Package 'graphite'

Help Index

Convertion of PathwayLists into lists.

Description

Usage

Arguments

Value

Author(s)

See Also

Examples

Build a Pathway object.

Description

Usage

Arguments

Value

Examples

Convert the node identifiers of a pathway.

Description

Usage

Arguments

Value

See Also

Examples

Plot a pathway graph in Cytoscape

Description

Usage

Arguments

Details

Value

See Also

Examples

Class "Pathway"

Description

Variants

Methods

Author(s)

See Also

Examples

List the available pathway databases.

Description

Usage

Value

Author(s)

See Also

Examples

Graph representing the topology of a pathway

Description

Usage

Arguments

Value

See Also

Examples

Class "PathwayList"

Description

Extends

Methods

Author(s)

See Also

Retrieve a list of pathways.

Description

Usage

Arguments

Value

See Also

Examples

Class "Pathways"

Description

Objects from the Class

Methods

Author(s)

See Also

Prepare pathway dataset needed by runSPIA.

Description

Usage

Arguments

Value

References

See Also

Run SPIA analysis

Description

Class `"Pathway"`

Class `"PathwayList"`

Class `"Pathways"`