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@darmitage
darmitage / diversityprofile
Created November 17, 2011 23:23
Calculate Diversity Profile
#Example for calculating diversity profiles of Part of the Eectronic Supplementary Material for Leinster, T. & Cobbold C.A. 2011
#"Measuring diversity: the importance of species similarity" #
#URL: www.esajournals.org/doi/abs/10.1890/10-2402.1 #
require(picante)
#assumes you already have a phylogeny (called "phylo") and a community matrix (called "samp")#
#where rows = sites, columns = taxa (the way VEGAN and PICANTE like them).#
samp <- t(samp)
@darmitage
darmitage / bipartite code
Created November 1, 2011 21:00
Bipartite network Code
#This code uses a community matrix a'la VEGAN to make a bipartite network of how your taxa are organized into a particular habitat#
#Gets really messy with >100 species#
samp <- samp[c(4,10,1,11,12),]
require(bipartite)
visweb(samp, type="nested", prednames=TRUE, preynames=TRUE, labsize=1,
plotsize=12, square="black", text="no", frame=NULL, textsize=1,
textcol="red", pred.lablength=NULL, prey.lablength = NULL, clear=TRUE,
@darmitage
darmitage / cyanodiversity
Created November 1, 2011 20:56
Phylodiversity plots
#This is code for those plots I made using the MPD and MNTD metrics. You need to organize them into a table such as the one below#
require(ggplot2)
data = read.csv("data.csv", header = TRUE, sep = "")
s <- c("NM1","NM2","NM3", "NM4", "NM5", "Green", "Pink", "Brown", "S1", "S2", "G1", "G2")
data$OTU <- factor(data$OTU)
cyanos = subset(data, group == "cyano")
PSBs = subset(data, group == "PSB")
closts = subset(data, group == "clost")
@darmitage
darmitage / cyanonest
Created November 1, 2011 20:49
Nestedness Code
############################################################################
#CODE FOR ANALYZING NESTEDNESS OF A COMMUNITY MATRIX & PLOTTING THE RESULTS#
############################################################################
require(vegan)
require(ade4)
#Here, samp_85 is simply a community matrix of my 85% OTU cyano bins. The [5:9] just chooses
#specific rows for analysis (here, a depth gradient).
samp <- samp_85[c(5:9),]