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x_ExampleR_4_Format.for.PRIMER.R
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x_ExampleR_4_Format.for.PRIMER.R
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###### Making PRIMER formated data from EventMeasure queries ######
### Written by Tim Langlois
### Any errors are due to Tim Langlois
### Please forward any updates and improvements to [email protected]
# The following code forms an appendix to the manuscript:
# "McLean et al. 2016. Distribution, Abundance, Diversity and Habitat Associations of Fishes across a Bioregion Experiencing Rapid Coastal Development.â Estuarine, Coastal and Shelf Science 178 (September): 36â47"
# Please cite it if you like it
### objective is to
# 1. Format data to PRIMER format - with samples as Rows and Species as coloums
# 2. With Factors, to the right, and Indicators, below, seperated by blank columns and rows respectively.
# 3. This is really hard to do in R!
# Naming conventions----
# data objects in lower case
# column names Capitalized
# Libraries required
detach("package:plyr", unload=TRUE)#will error - no worries
library(tidyr)
library(dplyr)
options(dplyr.width = Inf) #enables head() to display all coloums
library(ggplot2)
library(readxl)
library(googlesheets)
# Set directories----
rm(list=ls())
study<-"x_Example_BRUV"
# Add you work dir here-
work.dir=("C:/Tims Documents/ownCloud/GitHub_Example")
# work.dir=("~/ownCloud/GitHub_Example")
tidy.data=paste(work.dir,"Data/Tidy data",sep="/")
primer.data=paste(work.dir,"Data/PRIMER data",sep="/")
# Functions----
# For PRIMER - Append blank column to distiguish Factors--
append_col <- function(x, cols, after=length(x)) {
x <- as.data.frame(x)
if (is.character(after)) {
ind <- which(colnames(x) == after)
if (any(is.null(ind))) stop(after, "not found in colnames(x)\n")
} else if (is.numeric(after)) {
ind <- after
}
stopifnot(all(ind <= ncol(x)))
cbind(x, cols)[, append(1:ncol(x), ncol(x) + 1:length(cols), after=ind)]
}
# Bring in the long data - with habitat-----
setwd(tidy.data)
dir()
primer.species<-read.csv("x_Example_BRUV_combined.factors.habitat.csv")%>%
filter(Group=="Species")%>%
group_by(Taxa,Sample) %>%
summarise(Abundance = sum(Value))%>%
spread(Taxa,Abundance, fill = 0)%>%
select(-Total, -Rich, everything())
head(primer.species)
primer.species.factors.habitat<-read.csv("x_Example_BRUV_combined.factors.habitat.csv")%>%
select(-Taxa,-Value,-Group,-Measure)%>%
distinct()%>%
left_join(primer.species,.,,by="Sample")%>%
append_col(., list(blank=NA), after="Total")
head(primer.species.factors.habitat)
primer.habitat<-read.csv("x_Example_BRUV_combined.factors.habitat.csv")%>%
select(-Taxa,-Value,-Group,-Measure)%>%
distinct()%>%
select(-c(CampaignID,Location,Status,Site,Method), everything())%>%
append_col(., list(blank=NA), after="broad.Reef")
head(primer.habitat)
names(primer.habitat)
# Bring in the Indicators - Family/Feeding to put below the data----
gs_ls()
Life_history <- gs_title("Life_history")#register a sheet
history<-Life_history%>%
gs_read_csv(ws = "Life_history")%>%
filter(grepl('Australia', Global.region))%>%
filter(grepl('Ningaloo|Pilbara', Local.region))%>%
select(Genus_species,Family,Feeding.guild,Targeted)
head(history,7)
# Make the Indicators----
indicators<-read.csv("x_Example_BRUV_combined.factors.habitat.csv")%>%
filter(Group=="Species")%>%
select(Taxa)%>%
distinct()%>%
left_join(history,by=c("Taxa"="Genus_species"))
head(indicators)
indicators.t<-setNames(data.frame(t(indicators[,-1])),indicators[,1])%>%
add_rownames("Sample")
head(indicators.t)
# Make the blank row----
temp.row<-matrix(c(rep.int("",length(primer.species.factors.habitat))),nrow=1,ncol=length(primer.species.factors.habitat))
blank.row<-data.frame(temp.row)
colnames(blank.row)<-colnames(primer.species.factors.habitat)
head(blank.row)
# Make the final PRIMER data----
primer.species.factors.habitat[]<-lapply(primer.species.factors.habitat,as.character) #have to make whole data.frame as.character
primer<-primer.species.factors.habitat%>%
bind_rows(blank.row,indicators.t)
tail(primer)
# Write PRIMER data----
setwd(primer.data)
# For PRIMER - Make "blank" name blank - this can ONLY be done with plyr()---
detach("package:dplyr", unload=TRUE) #this fixes names of value problem
detach("package:plyr", unload=TRUE) #this fixes names of value problem
library(plyr) #plyr can do this be dplyr can't!
primer <- rename(primer, replace =c("blank"="") )
head(primer)
write.csv(primer,file=paste(study,"PRIMER.csv",sep = "_"), row.names=FALSE)
primer.habitat <- rename(primer.habitat, replace =c("blank"="") )
head(primer.habitat)
write.csv(primer.habitat,file=paste(study,"PRIMER.Habitat.csv",sep = "_"), row.names=FALSE)