library("picante") library("adegenet") library("devtools") library("ggplot2") ##### ####Importing data - Must change file extension manually obj1 <- import2genind("populations.snps.gen") #Turning genpop file into csv sum(is.na(obj1$tab)) Symbio_Genpop <- tab(obj1, freq = TRUE, NA.method = "mean") write.csv(Symbio_Genpop,file="Symbio_Genpop.csv") ##### #Mantel test for Sanger and 2b-RAD #Read tree into object phylo <-read.tree(choose.files()) phylo #Read 2b-RAD data into object comm <- read.csv(choose.files(), header = TRUE, row.names = 1) comm[1:5, 1:5] #attributes(comm) #Use this to automatically reorder rows using tree and community data (i.e. 2b-RAD genpop data) #check for mismatches/missing species #using .data instead of .comm since community data is in data.frame class combined <- match.phylo.data(phylo, comm) # the resulting object is a list with $phy and $comm elements. replace our # original data with the sorted/matched data phy <- combined$phy comm <- combined$data #this needs to be $data and not $comm since we used the ".data" ending #attributes(phy) #write comm data to new csv write.csv(comm, file = "Zoa_2bRAD_matched_to_tree.csv") #Get distances between terminal nodes) Zoa_Tree_Distance <-cophenetic.phylo(phy) write.csv(Zoa_Tree_Distance, file = "Zoa_Tree_matched_to_RAD.csv") #Read in our csv files RawRAD=read.csv(choose.files(),header=TRUE, row.names=1) Sanger=read.csv(choose.files(),header=TRUE, row.names=1) #2b-RAD data needs to be transformed into Distance matrix RAD <- vegdist(RawRAD, method="euclidean", binary=FALSE, diag = TRUE, na.rm = FALSE) Sangerveg <- vegdist(Sanger, method = "euclidean", binary = FALSE, diag = TRUE, na.rm = FALSE) #Note that in the RAD data since it is a "dist" class the sample names are known as "labels" not rownames all.equal(labels(RAD),labels(Sangerveg)) mantel(RAD, Sanger) ##### #Comparing Zoa 2b-RAD to Symbio 2b-RAD Zoa_RAD_Excel <- read.csv(choose.files(), header = TRUE, row.names=1) Symbio_RAD_Excel <- read.csv(choose.files(), header = TRUE, row.names = 1) #Trying to remove samples from Zoa data that are not in Symbio data #Doing this manually since sample names do not match Zoa_RAD_Excel[1:8, 1:8] Symbio_RAD_Excel[1:8, 1:8] Zoa_rm_rows <- Zoa_RAD_Excel[-c(7,8,10,13),] Zoa_rm_rows[1:16,1:16] Symbio_veg <- vegdist(Symbio_RAD_Excel, method="euclidean", binary=FALSE, diag = TRUE, na.rm = FALSE) Zoa_veg <- vegdist(Zoa_rm_rows, method="euclidean", binary=FALSE, diag = TRUE, na.rm = FALSE) Zoa_veg Symbio_veg #this wont work since names do not match up #all.equal(labels(Zoa_veg),labels(Symbio_veg)) #Get both data sets into distance matrix mantel(Zoa_veg, Symbio_veg) ##### #Getting morphological data in morpho <- read.csv(choose.files(), header = TRUE, row.names=1) morpho #Have to match up sample names with tree file #Mantel Test with Sanger and morpho data #Read tree into object phylo_m <-read.tree(choose.files()) phylo_m #check for mismatches/missing species #using .data instead of .comm since community data is in data.frame class combined_m <- match.phylo.data(phylo_m, morpho) # the resulting object is a list with $phy and $comm elements. replace our # original data with the sorted/matched data phy_morpho <- combined_m$phy morpho_matched_sanger <- combined_m$data #this needs to be $data and not $comm since we used the ".data" ending #Writing morpho metrics to csv in new order write.csv(morpho_matched_sanger, file = "morpho_color_matched_to_sanger.csv") #Writing tree to new csv because it's now matched to morpho data Zoa_tree_to_morpho <-cophenetic.phylo(phy_morpho) write.csv(Zoa_tree_to_morpho, file = "tree_matched_to_morpho_color.csv") #Read in CSVs and check sample order morpho_reordered=read.csv(choose.files(),header=TRUE, row.names=1) Sanger_morpho=read.csv(choose.files(),header=TRUE, row.names=1) all.equal(row.names(morpho_reordered),rownames(Sanger_morpho)) morpho_dist <- vegdist(morpho_reordered, method="euclidean", binary=FALSE, diag = TRUE, na.rm = FALSE) morpho_dist Sanger_veg <- vegdist(Sanger_morpho, method = "euclidean", binary = FALSE, diag = TRUE, na.rm = FALSE) Sanger_veg morph_color_sanger_mantel <- mantel(morpho_dist, Sanger_veg) morph_color_sanger_mantel ##### #Mantel test for Morpho and 2b-RAD data morpho_r <- read.csv(choose.files(), header = TRUE, row.names=1) RAD_r <- read.csv(choose.files(), header = TRUE, row.names = 1) ##### #This section is for matching Symbiodinium RAD data to Zoa Morpho morpho_r RAD_r[1:16,1:16] morpho_rm <- morpho_r[-c(4,8,9,11,12,15),] morpho_rm morpho_rm_veg <- vegdist(morpho_rm, method="euclidean", binary=FALSE, diag = TRUE, na.rm = FALSE) Symbio_RAD_veg <- vegdist(RAD_r, method="euclidean", binary=FALSE, diag = TRUE, na.rm = FALSE) mantel(morpho_rm_veg, Symbio_RAD_veg) ##### #Section for morpho to Zoa RAD data #Trying to remove samples from morpho data that are not in RAD data matched_morpho_r <- morpho_r[rownames(morpho_r) %in% rownames(RAD_r),] matched_morpho_r all.equal(rownames(RAD_r),rownames(matched_morpho_r)) #Get both data sets into distance matrix morpho_r_dist <- vegdist(matched_morpho_r, method="euclidean", binary=FALSE, diag = TRUE, na.rm = FALSE) morpho_r_dist RAD_r_dist <- vegdist(RAD_r, method="euclidean", binary=FALSE, diag = TRUE, na.rm = FALSE) RAD_r_dist mantel(morpho_r_dist, RAD_r_dist)