ICGE (version 0.4.2)

dproc2: Modified Procrustes distance

Description

dproc2 computes and returns all the pairwise procrustes distances between genes in a time course experiment, using their expression profile.

Usage

dproc2(x, timepoints = NULL)

Value

A dist object with distance information.

Arguments

x

a matrix containing, in its rows, the gene expression values at the T considered time points.

timepoints

a T-vector with the T observed time points. If timepoints=NULL (default), then timepoints=1:T.

Author

Itziar Irigoien ; Konputazio Zientziak eta Adimen Artifiziala, Euskal Herriko Unibertsitatea (UPV/EHU), Donostia, Spain.

Conchita Arenas ; Departament d'Estadistica, Universitat de Barcelona, Barcelona, Spain.

Details

Each row i of matrix x is arranged in a two column matrix Xi. In Xi, the first column contains the time points and the second column the observed gene expression values (xi1...).

References

Irigoien, I. , Vives, S. and Arenas, C. (2011). Microarray Time Course Experiments: Finding Profiles. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8(2), 464--475.

Gower, J. C. and Dijksterhuis, G. B. (2004) Procrustes Problems. Oxford University Press.

Sibson, R. (1978). Studies in the Robustness of Multidimensional Scaling: Procrustes statistic. Journal of the Royal Statistical Society, Series B, 40, 234--238.

See Also

dist, dmahal, dgower, dcor dbhatta

Examples

# Given  10  hypothetical time course profiles
# over 6 time points at 1, 2, ..., 6 hours.
x <- matrix(c(0.38, 0.39, 0.38, 0.37, 0.385, 0.375,
              0.99, 1.19, 1.50, 1.83, 2.140, 2.770,
              0.38, 0.50, 0.71, 0.72, 0.980, 1.010,
              0.20, 0.40, 0.70, 1.06, 2.000, 2.500,
              0.90, 0.95, 0.97, 1.50, 2.500, 2.990,
              0.64, 2.61, 1.51, 1.34, 1.330 ,1.140,
              0.71, 1.82, 2.28, 1.72, 1.490, 1.060,
              0.71, 1.82, 2.28, 1.99, 1.975, 1.965,
              0.49, 0.78, 1.00, 1.27, 0.590, 0.340,
              0.71,1.00, 1.50, 1.75, 2.090, 1.380), nrow=10, byrow=TRUE)

# Graphical representation
matplot(t(x), type="b")

# Distance matrix between them
d <- dproc2(x)