calc_PDDmatrix: Calculate Pairwise Distance Deviation Matrix

In v-julia/recDplot: Visualisation of recombination events in nucleotide sequences using pairwise distance plots

Calculate Pairwise Distance Deviation Matrix

Description

Returns pairwise distance deviation matrix. To build such matrix, the sliding window is moved along the alignment, and for each window the pairwise genetic distances between sequences are calculated. Then for each pair of windows the linear regression for pairwise genetic distances is built and the root mean square error of linear regression is estimated.

Usage

calc_PDDmatrix(dna_object, step, window, method, modification = NA)

Arguments

dna_object	list of DNA sequences produced by read.dna function of ape package (as.character = TRUE mode)
step	step size for sliding process
window	window size (length of genomic regions)
method	method of calculation distances ("pdist", "JC", "Kimura", "TN")
modification	pairwise deletion of positions with gaps (modification='pairwise') or not (modification='NA')

Value

matrix

Examples

## Not run: 
library(colorRamps)
library(gplots)
alignment = read.dna(path/to/file, format="fasta", as.character=TRUE)
alignment[alignment=='-'] <- NA
pddmatrix = calc_PDDmatrix(alignment, 1, 500, 600, 1000)
heatmap.2(as.matrix(pddmatrix), Rowv = FALSE, Colv = "Rowv",
dendrogram = 'none', col=matlab.like, main="PDD matrix", tracecol=NA)
## End(Not run)

v-julia/recDplot documentation built on Feb. 20, 2024, 1:59 p.m.