FIFTH: Indel distances following the fifth state rationale

Description

This function computes an indel distance matrix following the rationale of the fifth state. For that, each gap within the alignment is treated as an independent mutation event.

Usage

FIFTH(inputFile = NA, align = NA, saveFile = T,
outname = paste(inputFile,"IndelDistanceFifthState.txt",
 sep = "_"), addExtremes = F)

Arguments

inputFile

the name of the fasta file to be analysed.

align

the name of the alignment to be analysed. See "read.dna" in ape package for details about reading alignments.

saveFile

a logical; if TRUE (default), function output is saved as a text file.

outname

if "saveFile" is set to TRUE (default), contains the name of the output file.

addExtremes

a logical; if TRUE, additional nucleotide sites are included in both extremes of the alignment. This will allow estimating distances for alignments showing gaps in terminal positions.

Value

A matrix containing the genetic distances estimated as indels pairwise differences.

Details

It is recommended to estimate this distance matrix after removing repeated sequences from the alignment. Repeated sequences increase computation time but do not provide additional information (because they produce duplicated rows and columns in the final distance matrix).

Examples

Run this code

cat(">Population1_sequence1",
"A-AGGGTC-CT---G",
">Population1_sequence2",
"TAA---TCGCT---G",
">Population1_sequence3",
"TAAGGGTCGCT---G",
">Population1_sequence4",
"TAA---TCGCT---G",
">Population2_sequence1",
"TTACGGTCG---TTG",
">Population2_sequence2",
"TAA---TCG---TTG",
">Population2_sequence3",
"TAA---TCGCTATTG",
">Population2_sequence4",
"TTACGGTCG---TTG",
">Population3_sequence1",
"TTA---TCG---TAG",
">Population3_sequence2",
"TTA---TCG---TAG",
">Population3_sequence3",
"TTA---TCG---TAG",
">Population3_sequence4",
"TTA---TCG---TAG",
     file = "ex3.fas", sep = "")

# Reading the alignment directly from file and saving no output file:
FIFTH (align=read.dna("ex3.fas",format="fasta"), saveFile = FALSE)

# Analysing the same dataset, but using only unique sequences:
uni<-GetHaplo(inputFile="ex3.fas",saveFile=FALSE)
FIFTH (align=uni, saveFile = FALSE)