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library(dplyr) | |
library(ggmap) | |
library(ggsn) | |
#Download map data for South Bimini | |
pngMAP_df <- get_map(location = c(lon = -79.275, lat = 25.71), | |
source = "google", | |
zoom = 13, | |
color="bw", |
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# aRe We There Yet (RWTY) Tutorial | |
# Bayesian Phylogenetic Inference using Markov Chain Monte Carlo (mcmc) | |
### Introduced in late 90s, now wildly popular | |
### Implemented in many software packages: MrBayes, BEAST, PhlyoBayes | |
# Phylogenetic inference computationally expensive, number of possible | |
# rooted trees for 60 taxa > number of protons in known universe | |
# Exhausitive tree search via optimality criteria such as maximum parsimony | |
# or maximum liklihood is NP-Hard |
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########################################### | |
# Functions for the analysis of AFLP data # | |
# Anthony J Geneva # | |
# 9 April 2013 # | |
########################################### | |
########################################### | |
# This function converts the binary table | |
# output from RawGeno to a format that can | |
# be read by AFLPScore |
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# This function converts the binary table output from | |
# RawGeno to a format that can be read by AFLPScore | |
################################## | |
# RawGeno_2_AFLPscore function # | |
################################## | |
RawGeno_2_AFLPscore <- function(outfilename) | |
{ |
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library(vegan) | |
class <- "Anthony" | |
dat <- read.table(paste(class,".dat", sep=""), sep = "\t", header=TRUE) | |
#######PieChart############ | |
piedata <- matrix(ncol=1, nrow=length(unique(dat[,1]))) | |
names <- levels(unique(dat[,1])) | |
rownames(piedata) <- names |