Mercurial > repos > ecology > tool_anonymization

comparison graph_stat_presence_abs.r @ 0:c586703ea141 draft default tip

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"planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 60627aba07951226c8fd6bb3115be4bd118edd4e"
author ecology
date Fri, 13 Aug 2021 18:13:54 +0000
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1 #Rscript
2
3 ################################
4 ## Median and dispersion ##
5 ################################
6
7 #####Packages : Cowplot
8 # ggplot2
9
10 #####Load arguments
11
12 args <- commandArgs(trailingOnly = TRUE)
13
14 if (length(args) == 0) {
15 stop("This tool needs at least one argument")
16 }else{
17 table <- args[1]
18 hr <- args[2]
19 var <- as.numeric(args[3])
20 spe <- as.numeric(args[4])
21 loc <- as.numeric(args[5])
22 time <- as.numeric(args[6])
23 source(args[7])
24 }
25
26 if (hr == "false") {
27 hr <- FALSE
28 }else{
29 hr <- TRUE
30 }
31
32 #####Import data
33 data <- read.table(table, sep = "\t", dec = ".", header = hr, fill = TRUE, encoding = "UTF-8")
34 data <- na.omit(data)
35 colvar <- colnames(data)[var]
36 colspe <- colnames(data)[spe]
37 colloc <- colnames(data)[loc]
38 coltime <- colnames(data)[time]
39
40 data <- data[grep("^$", data[, spe], invert = TRUE), ]
41
42 #####Your analysis
43
44 ####Median and data dispersion####
45
46 #Median
47 graph_median <- function(data, var) {
48 graph_median <- ggplot2::ggplot(data, ggplot2::aes_string(y = var)) +
49 ggplot2::geom_boxplot(color = "darkblue") +
50 ggplot2::theme(legend.position = "none") + ggplot2::ggtitle("Median")
51
52 return(graph_median)
53
54 }
55
56 #Dispersion
57 dispersion <- function(data, var, var2) {
58 graph_dispersion <- ggplot2::ggplot(data) +
59 ggplot2::geom_point(ggplot2::aes_string(x = var2, y = var, color = var2)) +
60 ggplot2::scale_fill_brewer(palette = "Set3") +
61 ggplot2::theme(legend.position = "none", axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust = 1), plot.title = ggplot2::element_text(color = "black", size = 12, face = "bold")) + ggplot2::ggtitle("Dispersion")
62
63 return(graph_dispersion)
64
65 }
66
67 #The 2 graph
68 med_disp <- function(med, disp) {
69 graph <- cowplot::plot_grid(med, disp, ncol = 1, nrow = 2, vjust = -5, scales = "free")
70
71 ggplot2::ggsave("Med_Disp.png", graph, width = 12, height = 20, units = "cm")
72 }
73
74
75 #### Zero problem in data ####
76
77 #Put data in form
78
79 data_num <- make_table_analyse(data, colvar, colspe, colloc, coltime)
80 nb_spe <- length(unique(data[, spe]))
81 nb_col <- ncol(data_num) - nb_spe + 1
82 data_num <- data_num[, nb_col:ncol(data_num)]
83
84 #Presence of zeros in the data
85 mat_corr <- function(data) {
86 cor(data)
87 }
88 p_mat <- function(data) {
89 ggcorrplot::cor_pmat(data)
90 } # compute a matrix of correlation p-values
91
92 graph_corr <- function(data_num) {
93 graph <- ggcorrplot::ggcorrplot(mat_corr(data_num), method = "circle", p.mat = p_mat(data_num), #barring the no significant coefficient
94 ggtheme = ggplot2::theme_gray, colors = c("#00AFBB", "#E7B800", "#FC4E07"))
95
96 ggplot2::ggsave("0_pb.png", graph)
97 }
98
99 ##Med and disp
100 med <- graph_median(data, var = colvar)
101 disp <- dispersion(data, var = colvar, var2 = colspe)
102 med_disp(med = med, disp = disp)
103
104 ##O problem
105 graph_corr(data_num)