SCORER2 (version 0.99.0)

scorer2: Predict oligomerization state of coiled-coil sequences

Description

Function for predicting the oligomeric state of a coiled-coil sequence

Usage

scorer2(id, seq, reg, pssm, delta=1)

Arguments

id

A vector of id names for each sequence to be predicted

seq

A vector of amino acid sequences; where each element of the vector is a character string of amino-acid sequence. Valid characters are all uppercase letters except ‘B’, ‘J’, ‘O’, ‘U’, ‘X’, and ‘Z’; invalid characters will not be tolerated and their use will result in a failure of the program.

reg

A character string denoting the heptad register of each amino acid sequence; valid characters are the lowercase letters ‘a’ to ‘g’. Register characters are not required to be in proper order. The register can start with any of the seven letters. It must always have the same length as the seq argument.

pssm

A profile scoring matrix generated from the SCORER 2.0 training data. You can either use the default one or create your own PSSM using the pssm.R function

delta

A numeric value strictly superior to 0 that serves as pseudocount in the profile scoring matrix. Empirical analysis has shown that a value of delta=1 is optimal.

Value

The function scorer2 is the most important one in the scorer2 package. It is used to apply the SCORER 2.0 prediction algorithm to predict the oligomeric state of a new coiled-coil sequence. By default the final classification is computed on the basis of the discriminant function value. If $f(x)>=0$, $x$ is predicted as a dimer, otherwise as trimer.

References

Craig T. Armstrong, Thomas L. Vincent, Peter J. Green and Dek N. Woolfson. (2011) SCORER 2.0: an algortihm for distinguishing parallel dimeric and trimeric coiled-coil sequences. Bioinformatics. DOI: 10.1093/bioinformatics/btr299

Examples

# load pssm data
data(pssm)

# predict oligomerization of GCN4 wildtype
GCN4wt.score <- scorer2("GCN4wt", "MKQLEDKVEELLSKNYHLENEVARLKKLV", 
		"abcdefgabcdefgabcdefgabcdefga", pssm,  delta=1)