Mercurial > repos > ecology > ecology_homogeneity_normality

annotate graph_homogeneity_normality.r @ 1:3df8937fd6fd 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 18:16:46 +0000
parents 9f679060051a
children
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9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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1 #Rscript
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9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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3 #######################################
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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4 ## Homogeneity and normality ##
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5 #######################################
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6
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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7 #####Packages : car
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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8 # ggplot2
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9 # ggpubr
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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10 # Cowplot
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11
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12 #####Load arguments
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14 args <- commandArgs(trailingOnly = TRUE)
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16 if (length(args) == 0) {
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17 stop("This tool needs at least one argument")
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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18 }else{
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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19 table <- args[1]
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20 hr <- args[2]
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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21 date <- as.numeric(args[3])
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22 spe <- as.numeric(args[4])
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23 var <- as.numeric(args[5])
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24 }
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26 if (hr == "false") {
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27 hr <- FALSE
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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28 }else{
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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29 hr <- TRUE
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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30 }
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32 #####Import data
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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33 data <- read.table(table, sep = "\t", dec = ".", header = hr, fill = TRUE, encoding = "UTF-8")
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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34 data <- na.omit(data)
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35 coldate <- colnames(data)[date]
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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36 colspe <- colnames(data)[spe]
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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37 colvar <- colnames(data)[var]
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38
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39 #####Your analysis
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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41 ####Homogeneity of the variance####
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43 ##Test of Levene##
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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44 testlevene <- function(data, col1, col2) {
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45 data[, col1] <- as.numeric(data[, col1])
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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46 data[, col2] <- as.factor(data[, col2])
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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47 tb_levene <- car::leveneTest(y = data[, col1], group = data[, col2])
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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49 return(tb_levene)
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50 }
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51 levene <- capture.output(testlevene(data = data, col1 = colvar, col2 = colspe))
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53 cat("\nwrite table with levene test. \n--> \"", paste(levene, "\"\n", sep = ""), file = "levene.txt", sep = "", append = TRUE)
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55 ##Two boxplots to visualize it##
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57 homog_var <- function(data, col1, col2, col3, mult) {
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58 data[, col1] <- as.factor(data[, col1])
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59 if (mult) {
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60 for (spe in unique(data[, col2])) {
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61 data_cut <- data[data[, col2] == spe, ]
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62 graph_2 <- ggplot2::ggplot(data_cut, ggplot2::aes_string(x = col1, y = col3, color = col1)) +
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63 ggplot2::geom_boxplot() +
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64 ggplot2::theme(legend.position = "none", axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust = 1), panel.background = ggplot2::element_rect(fill = "#d9d4c5", colour = "#d9d4c5", linetype = "solid"),
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65 panel.grid.major = ggplot2::element_line(linetype = "solid", colour = "white"),
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66 panel.grid.minor = ggplot2::element_line(linetype = "solid", colour = "white"))
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67
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68 ggplot2::ggsave(paste("Homogeneity_of_", spe, ".png"), graph_2, width = 16, height = 9, units = "cm")
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69 }
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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70 }else{
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71 graph_1 <- ggplot2::ggplot(data, ggplot2::aes_string(x = col1, y = col3, color = col1)) +
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72 ggplot2::geom_boxplot() +
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73 ggplot2::theme(legend.position = "none", axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust = 1))
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74
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75 #Put multiple panels
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76 graph_2 <- graph_1 + ggplot2::facet_grid(rows = ggplot2::vars(data[, col2]), scales = "free") +
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77 ggplot2::theme(panel.background = ggplot2::element_rect(fill = "#d9d4c5", colour = "#d9d4c5", linetype = "solid"),
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78 panel.grid.major = ggplot2::element_line(linetype = "solid", colour = "white"),
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79 panel.grid.minor = ggplot2::element_line(linetype = "solid", colour = "white"))
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80
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81 ggplot2::ggsave("Homogeneity.png", graph_2, width = 16, height = 9, units = "cm")
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82 }
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83 }
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84
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85 ####Normality of the distribution####
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86 # Kolmogorov-Smirnov test
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87
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88 ks <- capture.output(ks.test(x = data[, var], y = "pnorm", alternative = "two.sided"))
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89
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90 cat("\nwrite table with Kolmogorov-Smirnov test. \n--> \"", paste(ks, "\"\n", sep = ""), file = "ks.txt", sep = "", append = TRUE)
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91
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92 #Histogramm with distribution line
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93 graph_hist <- function(data, var1) {
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94 graph_hist <- ggplot2::ggplot(data) +
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95 ggplot2::geom_histogram(ggplot2::aes_string(x = var1), binwidth = 2, color = "black", fill = "white") +
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96 ggplot2::geom_density(ggplot2::aes_string(var1), alpha = 0.12, fill = "red") +
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97 ggplot2::ggtitle("Distribution histogram")
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98
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99 return(graph_hist)
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100 }
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101
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102 #Add the mean dashed line
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103 add_mean <- function(graph, var1) {
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104 graph_mean <- graph + ggplot2::geom_vline(xintercept = mean(data[, var1]),
9f679060051a "planemo upload for repository https://github.com/Marie59/Data_explo_tools commit 2f883743403105d9cac6d267496d985100da3958"
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105 color = "midnightblue", linetype = "dashed", size = 1)
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106
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107 return(graph_mean)
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108 }
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109
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110 #Adding a QQplot
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111 graph_qqplot <- function(data, var1) {
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112 graph2 <- ggpubr::ggqqplot(data, var1, color = "midnightblue") + ggplot2::ggtitle("Q-Q plot")
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113
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114 return(graph2)
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115 }
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116
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117 #On suppose que les données sont distribuées normalement lorsque les points suivent approximativement la ligne de référence à 45 degrés.
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118
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119 graph_fin <- function(graph1, graph2) {
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120 graph <- cowplot::plot_grid(graph1, graph2, ncol = 2, nrow = 1)
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121
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122 ggplot2::ggsave("Normal_distribution.png", graph, width = 10, height = 7, units = "cm")
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123 }
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124
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125 mult <- ifelse(length(unique(data[, colspe])) == 2, FALSE, TRUE)
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126 homog_var(data, col1 = coldate, col2 = colspe, col3 = colvar, mult = mult)
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127
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128 graph_hist1 <- graph_hist(data, var1 = colvar)
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129 graph_mean <- add_mean(graph = graph_hist1, var1 = colvar)
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130 graph_fin(graph1 = graph_mean, graph2 = graph_qqplot(data, var1 = colvar))