modEnrich: Module enrichment analysis.

In topherconley/spacemap: A novel conditional graphical model for integrative genomics

Description

Identify biological processes which are significantly-enriched in network modules.

Usage

modEnrich(ig, mods, levels = c("x", "y"), go2eg, glb = 15, minGO = 5,
  thresh = 0.05, adjust = "BH", prefix = "M", process_alias = NULL)

Arguments

ig	An igraph network object output from either adj2igraph, rankHub, cisTrans.
mods	modules with three accepted formats. An igraph object of class 'communities', which is typically the output of the cluster_* functions of igraph. A list where each element is a character vector that only contains the node identifiers from either yinfo$id or xinfo$id input to function adj2igraph. An integer vector with names as node identifiers and values as an integer. For example c(id1 = 1, id2 = 2, id3 = 2, id4 = 1).
levels	Any given module can contain x nodes or y nodes. If both predictors and responses have a functional mapping in the go2eg argument, then specify levels = c("x","y"). Otherwise, specify only those nodes that have a functional mapping. See details for more discussion.
go2eg	Named list where the names denote a biological process (e.g. Gene Ontology ID) and the elements of the list is a vector of members belonging to the biological process. The list ought to be non-redundant in names. For example, list(bio_proc_1 = c("gene1", "gene2", "gene3"), bio_proc_2 = c("gene4", "gene5", "gene6") )
glb	Integer defining the smallest possible size of a module in order for the module to be tested for enrichment.
minGO	Integer defining the smallest possible number of nodes represented in a biological process to be called a significant enrichment of that biological process.
thresh	Numeric between 0 and 1 indicating the threshold at which adjusted P-values should be considered significant.
adjust	Character of type stats::p.adjust.methods for specifying the type of multiple comparison adjustment desired.
prefix	Character to prefix module identifiers.
process_alias	Vector mapping biological process identifiers in go2eg with biologically meaningful descriptions. The vector process_alias must have names as the same names in go2eg and the elements are the biologically meaningful descriptions.

Details

The hyper-geometric test is used to test for over-representation of a biological process. In the phyper R function, parameter q is the overlap between the biological process group and the module, where the module is reduced to only its y node members if level = "y". Parameter m is the size of the biological process. Parameter n is the number of nodes in the network not in the biological process. This excluding node levels that do not have a functional mapping. In other words, if no x nodes do not appear in the mapping of go2eg, corresponding to level = "y", then x nodes are not counted, but "y" nodes without a mapping are counted, because most y nodes do have a mapping.

Value

A three-item list:

• The element "ig" is the input igraph network object updated with a "process_id" attribute for nodes affiliated with a significant GO-term. The "process_id" and "module" attributes together can be especially useful for visualizing which nodes of a module are enriched for a specific biological function.

• The element "etab" is the polished module enrichment table conveniently organized to report significant GO terms in modules, the representation of the GO term in the module relative to the size of the GO term, and what x-hubs may belong to the module.

• The element "eraw" contains details for each (module, GO-term) pair that was subjected to the hyper-geometric test. This output gives the user more control (if desired) over enrichment by reporting all tests, the relative over-representation of a GO-term in that module, the raw P-value, and the adjusted P-value.

See Also

adj2igraph, rankHub, cisTrans, reportHubs, xHubEnrich

topherconley/spacemap documentation built on May 31, 2019, 6:36 p.m.