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comparison indval.R @ 8:dcc059f387b6 draft default tip

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planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit 9dee19b2d28b61a81f2a89d4c7d35678e31a9927
author ecology
date Wed, 23 Jul 2025 14:37:01 +0000
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7:694738eda0dc 8:dcc059f387b6
1 #Seguineau Pauline
2 #02/12/2024
3 #Indicspecies tool
4
5 library(dplyr)
6 library(indicspecies)
7
8 #load arguments
9 args = commandArgs(trailingOnly=TRUE)
10 if (length(args)==0)
11 {
12 stop("This tool needs at least one argument")
13 }else{
14 clus_pts <- args[1]
15 occ <- args[2]
16 spe_name <- args[3]
17 sign <- args[4]
18 }
19
20 ###load data
21 clus <- read.table(clus_pts, dec=".", sep="\t", header=T,na.strings = "na") #cluster points file (ecoregionalization workflow)
22 data.col <- read.table(occ, dec=".", sep="\t", header=T,na.strings = "na") #occurrence file (merged table from ecoregionalization workflow)
23 spe_name = strsplit(spe_name, ",")
24 spname=NULL
25
26 for (n in spe_name) {
27 spname = cbind(names(data.col[as.numeric(n)]))}
28
29 #Rename decimalLatitude and decimalLongitude columns from occurrence file
30 if ("decimalLatitude" %in% colnames(data.col)) {
31 colnames(data.col)[which(colnames(data.col) == "decimalLatitude")] <- "lat"
32 }
33 if ("decimalLongitude" %in% colnames(data.col)) {
34 colnames(data.col)[which(colnames(data.col) == "decimalLongitude")] <- "long"
35 }
36
37 #Round lat and long of the data.col file to be able to put clus cluster in it
38 data.col$lat = round(data.col$lat,digits = 2)
39 data.col$long = round(data.col$long,digits = 2)
40
41 # Creates a new "station" column that associates a unique identifier to each latitude-longitude pair
42 data.col <- data.col %>% mutate(station = as.factor(paste(lat, long, sep = "_")))
43
44 # convert "station" to a unique numeric identifier
45 data.col <- data.col %>% mutate(station = as.numeric(factor(station)))
46
47 #Adding clusters to file
48 clusta <- merge(data.col,clus, by=c("lat","long"), all.x = TRUE)
49
50 #This generated duplicates with different clusters
51 clusta <- aggregate(clusta, by=list(clusta$station,clusta$cluster), FUN=mean, na.rm=TRUE)
52 clusta <- na.exclude(clusta)
53
54 # indval on all clusters
55 indval = multipatt(clusta[,spname], clusta$cluster,duleg = TRUE, control = how(nperm=999))
56 if (sign=="true"){
57 capture.output(summary(indval,indvalcomp=TRUE), file = "indval.txt")
58 }else{
59 capture.output(summary(indval,indvalcomp=TRUE, alpha=1), file = "indval.txt")}