GraphPAC (version 1.14.0)

Find.TSP.Path: Find.TSP.Path

Description

Employs a heuristic approach to solve the traveling salesman problem.

Usage

Find.TSP.Path(PositionList, mutation.matrix, insertion.type = "cheapest_insertion",
			  fix.start.pos = "Y")

Arguments

PositionList

A dataframe consisting of six columns: 1) Residue Name, 2) Amino Acid number in the protein, 3) Side Chain, 4) X-coordinate, 5) Y-coordinate and 6) Z-coordinate. Please see get.Positions and get.AlignedPositions in the iPAC package for further information on how to construct this matrix.

mutation.matrix

A matrix of 0's (no mutation) and 1's (mutation) where each column represents an amino acid in the protein and each row represents an individual sample (test subject, cell line, etc). Thus if column i in row j had a 1, that would mean that the ith amino acid for person j had a nonsynonomous mutation.

insertion.type

Specifies the type of insertion method used. Please see the TSP package for more details.

fix.start.pos

The TSP package starts the path at a random amino acid. Such that the results are easily reproducible, the default starts the path on the first amino acid in the protein.

Value

candidate.path

A numeric vector of the sequence found through the protein.

candidate.path.distance

The distance traveled along the candidate path.

dist.matrix

The distance matrix between any two pairwise amino acids.

linear.path.distance

The distance traveled if one were to visit the amino acids in the original sequence (1 -> 2 -> 3 -> ...->N

References

Michael Hahsler and Kurt Hornik (2011). Traveling Salesperson Problem (TSP) R package version 1.0-7. http://CRAN.R-project.org/.

Gregory Ryslik and Hongyu Zhao (2012). iPAC: Identification of Protein Amino acid Clustering. R package version 1.1.3. http://www.bioconductor.org/.

Examples

#Load the position and mutational data
CIF<-"http://www.pdb.org/pdb/files/3GFT.cif"
Fasta<-"http://www.uniprot.org/uniprot/P01116-2.fasta"
KRAS.Positions<-get.Positions(CIF,Fasta, "A")
data(KRAS.Mutations)

#Save all the results to path.results
path.results <- Find.TSP.Path(KRAS.Positions$Positions, KRAS.Mutations)