translate {bioCancer} | R Documentation

## Translate between different identifiers

### Description

Function for translating from one annotation to another, eg. from RefSeq to Ensemble. This function takes a vector of annotation values and translates first to the primary annotation in the Biocore Data Team package (ie. entrez gene identifier for org.Bt.eg.db) and then to the desired product, while removing non-translated annotations and optionally reducing the result so there is only a one-to-one relation.

### Usage

    translate(
      values,
      from,
      to = NULL,
      reduce = c("all", "first", "last"),
      return.list = TRUE,
      remove.missing = TRUE,
      simplify = FALSE,
      ...
    )

### Arguments

`values` | Vector of annotations that needs translation. Coerced to character vector.
`from` | Type of annotation `values` are given in. NB! take care in the orientation of the package, ie. if you have RefSeq annotations, use `org.Bt.egREFSEQ2EG` or (in some cases) `revmap(org.Bt.egREFSEQ)`.
`to` | Desired goal, eg. `org.Bt.egENSEMBLPROT`. If `NULL` (default), goal if the packages primary annotation (eg. entrez gene for org.Bt.eg.db). Throws a warning if the organisms in `from` and `to` are not the same.
`reduce` | Reducing method, either return all annotations (one-to-many relation) or the first or last found annotation. The reducing step is applied after translating to the goal: `all`: returns all annotations `first` or `last`: choose first or last of arbitrarily ordered list.
`return.list` | Logical, when `TRUE`, returns the translation as a list where names
`remove.missing` | Logical, whether to remove non-translated values, defaults `TRUE`.
`simplify` | Logical, unlists the result. Defaults to FALSE. Usefull when using `translate` in a `lapply` or `sapply`.
`...` | Additional arguments sent to `pickGO` if `from` returns GO set.

### Details

If you want to do some further mapping on the result, you will have to use either `unlist` og `lapply`, where the first returns all the end-products of the first mapping, returning a new list, and the latter produces a list-within-list.

If `from` returns GO identifiers (e.g. `from = org.Bt.egGO`), then the returned resultset is more complex and consists of several layers of lists instead of the usual list of character vectors. If `to` has also been specified, the GO IDs must be extracted (internally) and you have the option of filtering for evidence and category at this point. See `pickGO`.

### Value

List; names of elements are `values` and the elements are the translated elements, or `NULL` if not translatable with `remove.missing = TRUE`.

### Note

Requires user to deliver the annotation packages such as org.Bt.egREFSEQ.

### Author(s)

Stefan McKinnon Edwards stefan.hoj-edwards@agrsci.dk

### See Also

`pickRefSeq`, `pickGO`

### Examples

    library(org.Bt.eg.db)
    genes <- c(280705, 280706, 100327208)
    translate(genes, org.Bt.egSYMBOL)

    symbols <- c("SERPINA1","KERA","CD5")
    refseq <- translate(symbols, from=org.Bt.egSYMBOL2EG, to=org.Bt.egREFSEQ)
    # Pick the proteins:
    pickRefSeq(refseq, priorities=c('NP','XP'), reduce='all')

    # If you wanted do do some further mapping on the result from
    # translate, simply use lapply.

    library(GO.db)
    GO <- translate(genes, org.Bt.egGO)
    # Get all biological processes:
    pickGO(GO, category='BP')
    # Get all ontologies with experimental evidence:
    pickGO(GO, evidence=c('IMP','IGI','IPI','ISS','IDA','IEP','IEA'))

[Package bioCancer version 1.22.0 Index]