| distManhattan {micropan} | R Documentation |
Computing Manhattan distances between genomes
Description
Computes the (weighted) Manhattan distances beween all pairs of genomes.
Usage
distManhattan(pan.matrix, scale = 0, weights = rep(1, ncol(pan.matrix)))
Arguments
pan.matrix |
A pan-matrix, see |
scale |
An optional scale to control how copy numbers should affect the distances. |
weights |
Vector of optional weights of gene clusters. |
Details
The Manhattan distance is defined as the sum of absolute elementwise differences between two vectors. Each genome is represented as a vector (row) of integers in ‘pan.matrix’. The Manhattan distance between two genomes is the sum of absolute difference between these rows. If two rows (genomes) of the ‘pan.matrix’ are identical, the corresponding Manhattan distance is ‘0.0’.
The ‘scale’ can be used to control how copy number differences play a role in the distances computed. Usually we assume that going from 0 to 1 copy of a gene is the big change of the genome, and going from 1 to 2 (or more) copies is less. Prior to computing the Manhattan distance, the ‘pan.matrix’ is transformed according to the following affine mapping: If the original value in ‘pan.matrix’ is ‘x’, and ‘x’ is not 0, then the transformed value is ‘1 + (x-1)*scale’. Note that with ‘scale=0.0’ (default) this will result in 1 regardless of how large ‘x’ was. In this case the Manhattan distance only distinguish between presence and absence of gene clusters. If ‘scale=1.0’ the value ‘x’ is left untransformed. In this case the difference between 1 copy and 2 copies is just as big as between 1 copy and 0 copies. For any ‘scale’ between 0.0 and 1.0 the transformed value is shrunk towards 1, but a certain effect of larger copy numbers is still present. In this way you can decide if the distances between genomes should be affected, and to what degree, by differences in copy numbers beyond 1. Notice that as long as ‘scale=0.0’ (and no weighting) the Manhattan distance has a nice interpretation, namely the number of gene clusters that differ in present/absent status between two genomes.
When summing the difference across gene clusters we can also up- or downweight some clusters compared
to others. The vector ‘weights’ must contain one value for each column in ‘pan.matrix’. The
default is to use flat weights, i.e. all clusters count equal. See geneWeights for
alternative weighting strategies.
Value
A dist object (see dist) containing all pairwise Manhattan distances
between genomes.
Author(s)
Lars Snipen and Kristian Hovde Liland.
See Also
panMatrix, distJaccard, geneWeights.
Examples
# Loading a pan-matrix in this package
data(xmpl.panmat)
# Manhattan distances between genomes
Mdist <- distManhattan(xmpl.panmat)
## Not run:
# Making a dendrogram based on shell-weighted distances
library(ggdendro)
weights <- geneWeights(xmpl.panmat, type = "shell")
Mdist <- distManhattan(xmpl.panmat, weights = weights)
ggdendrogram(dendro_data(hclust(Mdist, method = "average")),
rotate = TRUE, theme_dendro = FALSE) +
labs(x = "Genomes", y = "Shell-weighted Manhattan distance", title = "Pan-genome dendrogram")
## End(Not run)