predict-methods {procoil} | R Documentation

## Predict oligomerization of one or more coiled coil segments

### Description

Function for predicting the oligomerization of one or multiple coiled coil segments

### Usage

    ## S4 method for signature 'CCModel'
    predict(object, seq, reg)

### Arguments

`object` | The model to be considered; can either be one of the models included in the package (`PrOCoilModel` and `PrOCoilModelBA`) or any other model loaded or created by the user. For a detailed explanation of the two default models, see `CCModel`.
`seq` | One or several amino acid sequences; valid characters are all uppercase letters except ‘B’, ‘J’, ‘O’, ‘U’, ‘X’, and ‘Z’; invalid characters are tolerated, but ignored by the prediction. This argument can be a character vector, an `AAString` object, an `AAStringSet` object, or an `AAVector` object
`reg` | a character vector containing the heptad register(s); valid characters are the lowercase letters ‘a’-‘g’ and dashes ‘-’. Can also be omitted, see details below.

### Details

The function `predict` is the most important one in the procoil package. It is used to apply a coiled coil prediction model to coiled coil sequences/segments. It uses the discriminant function described in `CCModel`. By default the final classification is computed on the basis of the discriminant function value f(x). If f(x)>=0, the sequence x is predicted as trimer, otherwise as dimer.

If the `reg` argument is missing, `predict` looks whether the object passed as argument `seq` includes heptad register information, either as an attribute `reg` (if `seq` is a character vector), as metadata field `reg` (if `seq` is an `AAString` or `AAStringSet` object), or via annotation metadata (if `seq` is an `AAStringSet` or `AAVector` object; see `annotationMetadata`). In any case, the `reg` argument has priority over all other ways of specifying the heptad annotation. In other words, if `reg` is specified and `seq` contains heptad annotations in one of the ways described above, the `reg` argument has priority and the heptad annotation in `seq` is ignored.

The `reg` argument must have exactly as many elements as `seq` has sequences, and the registers must be aligned to the sequences, i.e. the first register must be exactly as long as the first sequence, and so on.

If heptad registers contain dashes, the `predict` function extracts all contiguous coiled coil segments and computes predictions for all of them. The returned `CCProfile` object then contains profiles/predictions of all coiled coil segments that were extracted from `seq` (see example below).

### Value

returns a `CCProfile` object

### Author(s)

Ulrich Bodenhofer bodenhofer@bioinf.jku.at

### References

http://www.bioinf.jku.at/software/procoil/

Mahrenholz, C.C., Abfalter, I.G., Bodenhofer, U., Volkmer, R., and Hochreiter, S. (2011) Complex networks govern coiled coil oligomerization - predicting and profiling by means of a machine learning approach. Mol. Cell. Proteomics 10(5):M110.004994. DOI: 10.1074/mcp.M110.004994

### See Also

`procoil`, `CCModel`, `CCProfile`

### Examples

    ## predict oligomerization of GCN4 wildtype
    GCN4wt <- predict(PrOCoilModel,
                      "MKQLEDKVEELLSKNYHLENEVARLKKLV",
                      "abcdefgabcdefgabcdefgabcdefga")

    ## show result
    GCN4wt

    ## example with four GCN4 mutations
    GCN4mSeq <- c("GCN4wt"        ="MKQLEDKVEELLSKNYHLENEVARLKKLV",
                  "GCN4_N16Y_L19T"="MKQLEDKVEELLSKYYHTENEVARLKKLV",
                  "GCN4_E22R_K27E"="MKQLEDKVEELLSKNYHLENRVARLEKLV",
                  "GCN4_V23K_K27E"="MKQLEDKVEELLSKNYHLENEKARLEKLV")

    ## to illustrate the alternative interface, we convert this
    ## character vector to an 'AAStringSet' object and add
    ## heptad registers as annotation metadata
    GCN4mAA <- AAStringSet(GCN4mSeq)
    annotationMetadata(GCN4mAA, annCharset="abcdefg") <-
        rep("abcdefgabcdefgabcdefgabcdefga", 4)

    ## predict oligomerization (note: no 'reg' argument!)
    GCN4mut <- predict(PrOCoilModel, GCN4mAA)

    ## display summary of result
    GCN4mut

    ## predict oligomerization of unknown sequence (Marcoil example)
    MarcoilEx <- predict(PrOCoilModel,
       "MGECDQLLVFMITSRVLVLSTLIIMDSRQVYLENLRQFAENLRQNIENVHSFLENLRADLENLRQKFPGKWYSAMPGRHG",
       "-------------------------------abcdefgabcdefgabcdefgabcdefgabcdefg--------------")

    ## show results
    MarcoilEx

[Package procoil version 2.18.0 Index]