SCORER2 (version 0.99.0)

EstimateProbability: Estimate oligomeric state score of coiled-coil sequences

Description

Sub-function used in scorer2.R in order to compute the oligomeric state score of input coiled-coil sequences.

Usage

EstimateProbability(id, seq, reg, pssm, var, delta=1)

Arguments

id

A string that represents the id name of the test sequence

seq

A character string of the amino-acid sequence to be predicted. Valid characters are all uppercase letters except ‘B’, ‘J’, ‘O’, ‘U’, ‘X’, and ‘Z’;

reg

A character string of register assignements. Valid characters are the lowercase letters ‘a’ to ‘g’. Register characters are not required to be in proper order and may start with any of the seven letters. It must always have the same length as the matching amino-acid sequence.

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

var

A list of two elements containing all valid amino-acid and register characters.

delta

The pseudocount parameter introduced in the PSSM used for the estimation of oligomeric state scores. This helps avoid cases with zero count. Empirical analysis has shown that a default delta score of 1 is optimal.

Value

It is used to apply the SCORER 2.0 prediction algorithm to 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 a 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)

# define allowed amino and register characters
var <- list(
      amino = c("A","C","D","E","F","G","H","I","K","L",
      "M","N","P","Q","R","S","T","V","W","Y","X"),
      register = letters[1:7])
      
# run SCORER 2.0 on GCN4 wild-type
GCN4wt.score <- EstimateProbability("GCN4wt", 
			"MKQLEDKVEELLSKNYHLENEVARLKKLV", 
			"abcdefgabcdefgabcdefgabcdefga", 
			pssm, 
			var, 
			delta=1)