simLL {GOstats} | R Documentation

## Functions to compute similarities between GO graphs and also between Entrez Gene IDs based on their induced GO graphs.

### Description

Both `simUI` and `simLP` compute a similarity measure between two GO graphs. For `simLL`, first the induced GO graph for each of its arguments is found and then these are passed to one of `simUI` or `simLP`.

### Usage

    simLL(ll1, ll2, Ontology = "MF", measure = "LP", dropCodes = NULL,
          mapfun = NULL, chip = NULL)
    simUI(g1, g2)
    simLP(g1, g2)

### Arguments

`ll1` | A Entrez Gene ID as a character vector.
`ll2` | A Entrez Gene ID as a character vector.
`Ontology` | Which ontology to use ("MF", "BP", "CC").
`measure` | Which measure to use ("LP", "UI").
`dropCodes` | A set of evidence codes to be ignored in constructing the induced GO graphs.
`mapfun` | A function taking a character vector of Entrez Gene IDs as its only argument and returning a list of "GO lists" matching the structure of the lists in the GO maps of annotation data packages. The function should behave similarly to `mget(x, eg2gomap, ifnotfound=NA)`, that is, `NA` should be returned if a specified Entrez ID has no GO mapping. See details for the interaction of `mapfun` and `chip`.
`chip` | The name of a DB-based annotation data package (the name will end in ".db"). This package will be used to generate an Entrez ID to GO ID mapping instead of `mapfun`.
`g1` | An instance of the `graph` class.
`g2` | An instance of the `graph` class.

### Details

For each of `ll1` and `ll2` the set of most specific GO terms within the ontology specified (`Ontology`) that are not based on any excluded evidence code (`dropCodes`) are found. The mapping is achieved in one of three ways:

1. If `mapfun` is provided, it will be used to perform the needed lookups. In this case, `chip` will be ignored.
2. If `chip` is provided and `mapfun=NULL`, then the needed lookups will be done based on the Entrez to GO mappings encapsulated in the specified annotation data package. This is the recommended usage.
3. If `mapfun` and `chip` are `NULL` or missing, then the function will attempt to load the GO package (the environment-based package, distinct from GO.db). This package contains a legacy environment mapping Entrez IDs to GO IDs. If the GO package is not available, an error will be raised. Omitting both `mapfun` and `chip` is not recommended as it is not compatible with the DB-based annotation data packages.

Next, the induced GO graphs are computed.

Finally these graphs are passed to one of `simUI`, (union intersection), or `simLP` (longest path). For `simUI` the distance is the size of the intersection of the node sets divided by the size of the union of the node sets. Large values indicate more similarity. These similarities are between 0 and 1.

For `simLP` the length of the longest path in the intersection graph of the two supplied graph. Again, large values indicate more similarity. Similarities are between 0 and the maximum leaf depth of the graph for the specified ontology.

### Value

A list with:

`sim` | The numeric similarity measure.
`measure` | Which measure was used.
`g1` | The graph induced by `ll1`.
`g2` | The graph induced by `ll2`.

If one of the supplied Gene IDs does not have any GO terms associated with it, in the selected ontology and with the selected evidence codes then `NA` is returned.

### Author(s)

R. Gentleman

### See Also

`makeGOGraph`

### Examples

      library("hgu95av2.db")
      eg1 = c("9184", "3547")

      bb = simLL(eg1[1], eg1[2], "BP", chip="hgu95av2.db")

[Package GOstats version 2.4.0 Index]