{"id":17001,"date":"2020-06-27T23:56:45","date_gmt":"2020-06-27T22:56:45","guid":{"rendered":"https:\/\/www.datanovia.com\/en\/?p=17001"},"modified":"2020-06-27T23:56:45","modified_gmt":"2020-06-27T22:56:45","slug":"ajouter-des-p-values-aux-ggplot-facets-presentant-differentes-echelles","status":"publish","type":"post","link":"https:\/\/www.datanovia.com\/en\/fr\/blog\/ajouter-des-p-values-aux-ggplot-facets-presentant-differentes-echelles\/","title":{"rendered":"Ajouter des P-values aux GGPLOT Facets Pr\u00e9sentant Diff\u00e9rentes Echelles"},"content":{"rendered":"<div id=\"rdoc\">\n<p>Cet article d\u00e9crit comment calculer et ajouter automatiquement <strong>des p-values sur des ggplot facets avec diff\u00e9rentes \u00e9chelles<\/strong> en utilisant les packages R <em>ggpubr<\/em> et <em>rstatix<\/em>. Pour les graphiques multi-panneaux dont les \u00e9chelles de l\u2019axe des y sont \u00e0 peu pr\u00e8s similaires sur chaque panneau, vous pouvez suivre les \u00e9tapes d\u00e9crites dans cet article : <a href=\"https:\/\/www.datanovia.com\/en\/fr\/blog\/comment-ajouter-des-p-values-aux-graphiques-ggplot-avec-facet\/\">Comment Ajouter des P-values aux Graphiques GGPLOT avec Facet<\/a>.<\/p>\n<p>Ici, nous allons utiliser une donn\u00e9e de d\u00e9monstration pour cr\u00e9er des panneaux de graphiques avec des \u00e9chelles y tr\u00e8s diff\u00e9rentes. Vous apprendrez comment calculer automatiquement les positions y des p-values lorsque l\u2019\u00e9chelle des facets est configur\u00e9e sur l\u2019option <code>free<\/code>. Des exemples sont repr\u00e9sent\u00e9s pour les box plots et les bar plots.<\/p>\n<p>Sommaire:<\/p>\n<div id=\"TOC\">\n<ul>\n<li><a href=\"#pr\u00e9requis\">Pr\u00e9requis<\/a><\/li>\n<li><a href=\"#pr\u00e9paration-des-donn\u00e9es\">Pr\u00e9paration des donn\u00e9es<\/a><\/li>\n<li><a href=\"#tests-statistiques\">Tests statistiques<\/a><\/li>\n<li><a href=\"#faire-un-ggplot-avec-des-\u00e9chelles-fixes\">Faire un ggplot avec des \u00e9chelles fixes<\/a><\/li>\n<li><a href=\"#faire-un-ggplot-avec-des-\u00e9chelles-libres\">Faire un ggplot avec des \u00e9chelles libres<\/a>\n<ul>\n<li><a href=\"#facet-wrap\">Facet wrap<\/a><\/li>\n<li><a href=\"#facet-grid\">Facet grid<\/a><\/li>\n<\/ul>\n<\/li>\n<li><a href=\"#conclusion\">Conclusion<\/a><\/li>\n<\/ul>\n<\/div>\n<div id=\"pr\u00e9requis\" class=\"section level2\">\n<h2>Pr\u00e9requis<\/h2>\n<p>Lisez l\u2019article apparent\u00e9 suivant : <a href=\"https:\/\/www.datanovia.com\/en\/fr\/blog\/comment-ajouter-des-p-values-aux-graphiques-ggplot-avec-facet\/\">Comment Ajouter des P-values aux Graphiques GGPLOT avec Facet<\/a>.<\/p>\n<p>Assurez-vous d\u2019avoir install\u00e9 les paquets R suivants:<\/p>\n<ul>\n<li><code>tidyverse<\/code> pour la manipulation et la visualisation des donn\u00e9es<\/li>\n<li><code>ggpubr<\/code> pour cr\u00e9er facilement des graphiques pr\u00eats \u00e0 la publication<\/li>\n<li><code>rstatix<\/code> contient des fonctions R facilitant les analyses statistiques.<\/li>\n<\/ul>\n<p>Commencez par charger les packages requis suivants:<\/p>\n<pre class=\"r\"><code>library(ggpubr)\r\nlibrary(rstatix)<\/code><\/pre>\n<\/div>\n<div id=\"pr\u00e9paration-des-donn\u00e9es\" class=\"section level2\">\n<h2>Pr\u00e9paration des donn\u00e9es<\/h2>\n<pre class=\"r\"><code># Transformer `dose` en variable factorielle\r\ndf &lt;- ToothGrowth\r\ndf$dose &lt;- as.factor(df$dose)\r\n# Ajouter une variable de regroupement al\u00e9atoire\r\ndf$group &lt;- factor(rep(c(\"grp1\", \"grp2\"), 30))\r\n# Ajoutez des valeurs extr\u00eamement \u00e9lev\u00e9es dans la colonne 1 aux lignes c(1, 3, 5).\r\ndf[c(1, 3, 5),  1] &lt;- c(500, 495, 505)\r\nhead(df, 3)<\/code><\/pre>\n<pre><code>##     len supp dose group\r\n## 1 500.0   VC  0.5  grp1\r\n## 2  11.5   VC  0.5  grp2\r\n## 3 495.0   VC  0.5  grp1<\/code><\/pre>\n<\/div>\n<div id=\"tests-statistiques\" class=\"section level2\">\n<h2>Tests statistiques<\/h2>\n<p>Faire un ggplot avec les variables <code>supp<\/code> et <code>group<\/code>, et comparer les niveaux de la variable <code>dose<\/code> sur l\u2019axe des x. Le test post hoc de Tukey est utilis\u00e9 pour les comparaisons par paires.<\/p>\n<pre class=\"r\"><code>stat.test &lt;- df %&gt;%\r\n  group_by(group, supp) %&gt;%\r\n  tukey_hsd(len ~ dose) \r\nstat.test <\/code><\/pre>\n<pre><code>## # A tibble: 12 x 11\r\n##   supp  group term  group1 group2 null.value estimate conf.low conf.high    p.adj p.adj.signif\r\n## * &lt;fct&gt; &lt;fct&gt; &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;       &lt;dbl&gt;    &lt;dbl&gt;    &lt;dbl&gt;     &lt;dbl&gt;    &lt;dbl&gt; &lt;chr&gt;       \r\n## 1 OJ    grp1  dose  0.5    1               0     6.32    0.275      12.4 0.0403   *           \r\n## 2 OJ    grp1  dose  0.5    2               0    11.3     5.26       17.3 0.000852 ***         \r\n## 3 OJ    grp1  dose  1      2               0     4.98   -1.06       11.0 0.112    ns          \r\n## 4 VC    grp1  dose  0.5    1               0  -286.   -548.        -23.5 0.0328   *           \r\n## 5 VC    grp1  dose  0.5    2               0  -276.   -539.        -14.0 0.0389   *           \r\n## 6 VC    grp1  dose  1      2               0     9.46 -253.        272.  0.995    ns          \r\n## # \u2026 with 6 more rows<\/code><\/pre>\n<\/div>\n<div id=\"faire-un-ggplot-avec-des-\u00e9chelles-fixes\" class=\"section level2\">\n<h2>Faire un ggplot avec des \u00e9chelles fixes<\/h2>\n<pre class=\"r\"><code># Cr\u00e9er des bar plots avec les niveaux de significativit\u00e9\r\n# Cacher les ns (non significatif)\r\n# Ajoutez 15 % d'espace entre les \u00e9tiquettes et la bordure sup\u00e9rieure du graphique\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"dose\", fun = \"mean_se\")\r\nggbarplot(\r\n  df, x = \"dose\", y = \"len\", fill = \"#00AFBB\",\r\n  add = \"mean_se\", facet = c(\"supp\", \"group\")\r\n  ) +\r\n  stat_pvalue_manual(stat.test, hide.ns = TRUE, tip.length = 0, step.increase = 0) +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/063-add-p-values-to-ggplot-facets-with-different-scales-multipanel-bar-plots-facet-grid-fixed-scales-1.png\" width=\"480\" \/><\/p>\n<\/div>\n<div id=\"faire-un-ggplot-avec-des-\u00e9chelles-libres\" class=\"section level2\">\n<h2>Faire un ggplot avec des \u00e9chelles libres<\/h2>\n<div id=\"facet-wrap\" class=\"section level3\">\n<h3>Facet wrap<\/h3>\n<p>Vous devez sp\u00e9cifier l\u2019option <code>scales = \"free\"<\/code> \u00e0 la fois dans les fonctions <code>add_xy_position()<\/code> et <code>ggbarplot()<\/code>.<\/p>\n<pre class=\"r\"><code>stat.test &lt;- stat.test %&gt;% \r\n  add_xy_position(x = \"dose\", fun = \"mean_se\", scales = \"free\")\r\nggbarplot(\r\n  df, x = \"dose\", y = \"len\", fill = \"#00AFBB\",\r\n  add = \"mean_se\", facet.by = c(\"supp\", \"group\")\r\n  ) +\r\n  facet_wrap(vars(supp, group), scales = \"free\") +\r\n  stat_pvalue_manual(stat.test, hide.ns = TRUE, tip.length = 0) +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/063-add-p-values-to-ggplot-facets-with-different-scales-multipanel-bar-plots-facet-wrap-free-scales-1.png\" width=\"480\" \/><\/p>\n<\/div>\n<div id=\"facet-grid\" class=\"section level3\">\n<h3>Facet grid<\/h3>\n<p>Lorsque l\u2019argument <code>scales = \"free\"<\/code> est ajout\u00e9 dans facet grid, les graphiques d\u2019une m\u00eame ligne ne peuvent pas avoir un axe des y diff\u00e9rent. De m\u00eame, il ne peut y avoir qu\u2019un seul axe des abscisses pour chaque colonne. En faisant appel \u00e0 la fonction <code>facet_wrap()<\/code>, chaque graphique est affich\u00e9 ind\u00e9pendamment, ce qui permet de rendre \u201clibre\u201d ses axes x et y.<\/p>\n<p>Facet grid est utile lorsque vous souhaitez comparer les graphiques d\u2019une m\u00eame cat\u00e9gorie, ce qui peut \u00eatre fait en configurant les m\u00eames \u00e9chelles d\u2019axes. En revanche, facet wrap est plus utile pour les graphiques qui sont plus ind\u00e9pendantes les unes des autres.<\/p>\n<p>Il existe deux solutions possibles pour personnaliser la position y des niveaux de significativit\u00e9.<\/p>\n<div id=\"solution-1-utiliser-loption-step.increase\" class=\"section level4\">\n<h4>Solution 1 : Utiliser l\u2019option step.increase<\/h4>\n<p>Le comportement par d\u00e9faut de la fonction <code>add_xy_position()<\/code> est de calculer automatiquement une valeur globale d\u2019augmentation de pas (<code>step.increase<\/code>) entre les crochets. Ce calcul suppose que les \u00e9chelles y des panneaux du graphique sont fixes.<\/p>\n<p>Dans la situation o\u00f9 vous voulez des \u00e9chelles libres, vous pouvez:<\/p>\n<ol style=\"list-style-type: decimal;\">\n<li>Param\u00e9trez l\u2019option \u201cstep.increase\u201d \u00e0 0 lors de l\u2019appel de la fonction <code>add_xy_position()<\/code>.<\/li>\n<li>Pr\u00e9cisez uniquement l\u2019option <code>step.increase<\/code> in the function <code>stat_pvalue_manual()<\/code>. Dans ce cas, l\u2019option step.increase sera adapt\u00e9 \u00e0 chaque panneau de graphique.<\/li>\n<\/ol>\n<pre class=\"r\"><code>stat.test &lt;- stat.test %&gt;% \r\n  add_xy_position(x = \"dose\", fun = \"mean_se\", step.increase = 0)\r\nbp &lt;- ggbarplot(\r\n  df, x = \"dose\", y = \"len\", fill = \"#00AFBB\", add = \"mean_se\",\r\n  facet.by = c(\"supp\", \"group\"), scales = \"free\"\r\n  ) \r\nbp +\r\n  stat_pvalue_manual(stat.test, hide.ns = TRUE, tip.length = 0, step.increase = 0.2) +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/063-add-p-values-to-ggplot-facets-with-different-scales-unnamed-chunk-5-1.png\" width=\"384\" \/><\/p>\n<\/div>\n<div id=\"solution-2-utiliser-loption-scales-free.\" class=\"section level4\">\n<h4>Solution 2 : Utiliser loption scales = \u201cfree\u201d.<\/h4>\n<p>Dans facet grid, les \u00e9chelles des panneaux de ggplot g\u00e9n\u00e9r\u00e9s ne sont pas totalement libres. Par cons\u00e9quent, vous aurez besoin de plus de personnalisation pour adapter l\u2019aspect de la position y du niveau de significativit\u00e9. Vous devrez jouer avec les options <code>step.increase<\/code> et <code>brachet.nudge.y<\/code> dans la fonction <code>stat_pvalue_manual()<\/code>.<\/p>\n<pre class=\"r\"><code># Graphique par d\u00e9faut\r\nstat.test &lt;- stat.test %&gt;% \r\n  add_xy_position(x = \"dose\", fun = \"mean_se\", scales = \"free\")\r\nbp &lt;- ggbarplot(\r\n  df, x = \"dose\", y = \"len\", fill = \"#00AFBB\", add = \"mean_se\",\r\n  facet.by = c(\"supp\", \"group\"), scales = \"free\"\r\n  ) \r\nbp +\r\n  stat_pvalue_manual(stat.test, hide.ns = TRUE, tip.length = 0) +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/063-add-p-values-to-ggplot-facets-with-different-scales-multipanel-bar-plots-facet-grid-free-scales-1.png\" width=\"480\" \/><\/p>\n<pre class=\"r\"><code># Augmenter le pas entre les crochets\r\nbp +\r\n  stat_pvalue_manual(\r\n    stat.test, hide.ns = TRUE, tip.length = 0,\r\n    step.increase = 0.1\r\n    ) +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/063-add-p-values-to-ggplot-facets-with-different-scales-multipanel-bar-plots-facet-grid-free-scales-2.png\" width=\"480\" \/><\/p>\n<pre class=\"r\"><code># Mettez les crochets en bas\r\n# Pr\u00e9cisez l'option bracket.nudge.y pour chacun des panels\r\n# Doit \u00eatre de la m\u00eame longueur que le nombre de comparaisons\r\nbracket.nudge.y &lt;- c(\r\n  -2, -3,               # Panel 1 : grp1\/OJ\r\n  -100, -160,           # Panel 2 : grp1\/VC\r\n  -10, -11,             # Panel 3 : grp2\/OJ\r\n  -250, -250, -250      # Panel 4 : grp2\/VC\r\n  )\r\nbp +\r\n  stat_pvalue_manual(\r\n    stat.test, hide.ns = TRUE, tip.length = 0,\r\n    step.increase = 0.09, bracket.nudge.y = bracket.nudge.y\r\n    ) +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/063-add-p-values-to-ggplot-facets-with-different-scales-multipanel-bar-plots-facet-grid-free-scales-3.png\" width=\"480\" \/><\/p>\n<\/div>\n<\/div>\n<\/div>\n<div id=\"conclusion\" class=\"section level2\">\n<h2>Conclusion<\/h2>\n<p>Cet article d\u00e9crit comment ajouter des p-values sur des ggplots facets avec diff\u00e9rentes \u00e9chelles sur l\u2019axe des y. Voir les autres questions fr\u00e9quemment pos\u00e9es : <a href=\"https:\/\/www.datanovia.com\/en\/fr\/blog\/tag\/ggpubr-fr\/\">ggpubr FAQ<\/a>.<\/p>\n<\/div>\n<\/div>\n<p><!--end rdoc--><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Cet article d\u00e9crit comment calculer et ajouter automatiquement des p-values sur des ggplot facets avec diff\u00e9rentes \u00e9chelles en utilisant les packages R ggpubr et rstatix. Pour les graphiques multi-panneaux dont [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":16997,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"rating_form_position":"","rating_results_position":"","mr_structured_data_type":"","footnotes":""},"categories":[342],"tags":[350],"class_list":["post-17001","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-faq-fr","tag-ggpubr-fr"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Ajouter des P-values aux GGPLOT Facets Pr\u00e9sentant Diff\u00e9rentes Echelles - Datanovia<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.datanovia.com\/en\/fr\/blog\/ajouter-des-p-values-aux-ggplot-facets-presentant-differentes-echelles\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Ajouter des P-values aux GGPLOT Facets Pr\u00e9sentant Diff\u00e9rentes Echelles - Datanovia\" \/>\n<meta property=\"og:description\" content=\"Cet article d\u00e9crit comment calculer et ajouter automatiquement des p-values sur des ggplot facets avec diff\u00e9rentes \u00e9chelles en utilisant les packages R ggpubr et rstatix. 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