{"id":15704,"date":"2020-04-11T10:29:03","date_gmt":"2020-04-11T09:29:03","guid":{"rendered":"https:\/\/www.datanovia.com\/en\/?p=15704"},"modified":"2020-04-13T14:14:13","modified_gmt":"2020-04-13T13:14:13","slug":"ggpubr-how-to-add-adjusted-p-values-to-a-multi-panel-ggplot","status":"publish","type":"post","link":"https:\/\/www.datanovia.com\/en\/blog\/ggpubr-how-to-add-adjusted-p-values-to-a-multi-panel-ggplot\/","title":{"rendered":"GGPUBR: How to Add Adjusted P-values to a Multi-Panel GGPlot"},"content":{"rendered":"<div class=\"rdoc\">\n<pre class=\"r\"><code># Load required R packages\r\nlibrary(ggpubr)\r\nlibrary(rstatix)\r\n\r\n# Data preparation\r\ndf &lt;- tibble::tribble(\r\n  ~sample_type, ~expression, ~cancer_type,   ~gene,\r\n      \"cancer\",        25.8,       \"Lung\", \"Gene1\",\r\n      \"cancer\",        25.5,      \"Liver\", \"Gene1\",\r\n      \"cancer\",        22.4,      \"Liver\", \"Gene1\",\r\n      \"cancer\",        21.2,       \"Lung\", \"Gene1\",\r\n      \"cancer\",        24.5,      \"Liver\", \"Gene1\",\r\n      \"cancer\",        27.3,      \"Liver\", \"Gene1\",\r\n      \"cancer\",        30.9,      \"Liver\", \"Gene1\",\r\n      \"cancer\",        17.6,     \"Breast\", \"Gene1\",\r\n      \"cancer\",        19.7,       \"Lung\", \"Gene1\",\r\n      \"cancer\",         9.7,     \"Breast\", \"Gene1\",\r\n      \"cancer\",        15.2,     \"Breast\", \"Gene2\",\r\n      \"cancer\",        26.4,      \"Liver\", \"Gene2\",\r\n      \"cancer\",        25.8,       \"Lung\", \"Gene2\",\r\n      \"cancer\",         9.7,     \"Breast\", \"Gene2\",\r\n      \"cancer\",        21.2,       \"Lung\", \"Gene2\",\r\n      \"cancer\",        24.5,      \"Liver\", \"Gene2\",\r\n      \"cancer\",        14.5,     \"Breast\", \"Gene2\",\r\n      \"cancer\",        19.7,       \"Lung\", \"Gene2\",\r\n      \"cancer\",        25.2,       \"Lung\", \"Gene2\",\r\n      \"normal\",        43.5,       \"Lung\", \"Gene1\",\r\n      \"normal\",        76.5,      \"Liver\", \"Gene1\",\r\n      \"normal\",        21.9,     \"Breast\", \"Gene1\",\r\n      \"normal\",        69.9,      \"Liver\", \"Gene1\",\r\n      \"normal\",       101.7,      \"Liver\", \"Gene1\",\r\n      \"normal\",        80.1,      \"Liver\", \"Gene1\",\r\n      \"normal\",        19.2,     \"Breast\", \"Gene1\",\r\n      \"normal\",        49.5,       \"Lung\", \"Gene1\",\r\n      \"normal\",        34.5,     \"Breast\", \"Gene1\",\r\n      \"normal\",        51.9,       \"Lung\", \"Gene1\",\r\n      \"normal\",        67.5,       \"Lung\", \"Gene2\",\r\n      \"normal\",          30,     \"Breast\", \"Gene2\",\r\n      \"normal\",        76.5,      \"Liver\", \"Gene2\",\r\n      \"normal\",        88.5,      \"Liver\", \"Gene2\",\r\n      \"normal\",        69.9,      \"Liver\", \"Gene2\",\r\n      \"normal\",        49.5,       \"Lung\", \"Gene2\",\r\n      \"normal\",        80.1,      \"Liver\", \"Gene2\",\r\n      \"normal\",        79.2,      \"Liver\", \"Gene2\",\r\n      \"normal\",        12.6,     \"Breast\", \"Gene2\",\r\n      \"normal\",        97.5,      \"Liver\", \"Gene2\",\r\n      \"normal\",        64.5,      \"Liver\", \"Gene2\"\r\n  )\r\n\r\n# Summary statistics\r\ndf %&gt;%\r\n  group_by(gene, cancer_type, sample_type) %&gt;%\r\n  get_summary_stats(expression, type = \"common\")<\/code><\/pre>\n<pre><code>## # A tibble: 12 x 13\r\n##    sample_type cancer_type gene  variable     n   min   max median   iqr  mean\r\n##    &lt;chr&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;dbl&gt;\r\n##  1 cancer      Breast      Gene1 express\u2026     2   9.7  17.6   13.6  3.95  13.6\r\n##  2 normal      Breast      Gene1 express\u2026     3  19.2  34.5   21.9  7.65  25.2\r\n##  3 cancer      Liver       Gene1 express\u2026     5  22.4  30.9   25.5  2.8   26.1\r\n##  4 normal      Liver       Gene1 express\u2026     4  69.9 102.    78.3 10.6   82.0\r\n##  5 cancer      Lung        Gene1 express\u2026     3  19.7  25.8   21.2  3.05  22.2\r\n##  6 normal      Lung        Gene1 express\u2026     3  43.5  51.9   49.5  4.2   48.3\r\n##  7 cancer      Breast      Gene2 express\u2026     3   9.7  15.2   14.5  2.75  13.1\r\n##  8 normal      Breast      Gene2 express\u2026     2  12.6  30     21.3  8.7   21.3\r\n##  9 cancer      Liver       Gene2 express\u2026     2  24.5  26.4   25.4  0.95  25.4\r\n## 10 normal      Liver       Gene2 express\u2026     7  64.5  97.5   79.2 11.1   79.5\r\n## 11 cancer      Lung        Gene2 express\u2026     4  19.7  25.8   23.2  4.53  23.0\r\n## 12 normal      Lung        Gene2 express\u2026     2  49.5  67.5   58.5  9     58.5\r\n## # \u2026 with 3 more variables: sd &lt;dbl&gt;, se &lt;dbl&gt;, ci &lt;dbl&gt;<\/code><\/pre>\n<pre class=\"r\"><code># Statistical test\r\n# group the data by cancer type and gene\r\n# Compare expression values of normal and cancer samples\r\nstat.test &lt;- df %&gt;%\r\n  group_by(cancer_type, gene) %&gt;%\r\n  t_test(expression ~ sample_type) %&gt;%\r\n  adjust_pvalue(method = \"bonferroni\") %&gt;%\r\n  add_significance()\r\nstat.test<\/code><\/pre>\n<pre><code>## # A tibble: 6 x 12\r\n##   cancer_type gene  .y.   group1 group2    n1    n2 statistic    df       p   p.adj\r\n## * &lt;chr&gt;       &lt;chr&gt; &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;  &lt;int&gt; &lt;int&gt;     &lt;dbl&gt; &lt;dbl&gt;   &lt;dbl&gt;   &lt;dbl&gt;\r\n## 1 Breast      Gene1 expr\u2026 cancer normal     2     3    -1.88   2.92 1.60e-1 9.60e-1\r\n## 2 Breast      Gene2 expr\u2026 cancer normal     3     2    -0.921  1.08 5.17e-1 1.00e+0\r\n## 3 Liver       Gene1 expr\u2026 cancer normal     5     4    -7.96   3.26 3.04e-3 1.82e-2\r\n## 4 Liver       Gene2 expr\u2026 cancer normal     2     7   -12.6    6.53 7.90e-6 4.74e-5\r\n## 5 Lung        Gene1 expr\u2026 cancer normal     3     3    -8.41   3.67 1.58e-3 9.48e-3\r\n## 6 Lung        Gene2 expr\u2026 cancer normal     4     2    -3.89   1.06 1.50e-1 9.00e-1\r\n## # \u2026 with 1 more variable: p.adj.signif &lt;chr&gt;<\/code><\/pre>\n<pre class=\"r\"><code># Create boxplot\r\nbxp &lt;- ggboxplot(\r\n  df, x = \"sample_type\", y = \"expression\", \r\n  facet.by = c(\"gene\", \"cancer_type\")\r\n  ) +\r\n  rotate_x_text(angle = 60)\r\n\r\n# Add adjusted p-values\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"sample_type\")\r\nbxp + stat_pvalue_manual(stat.test, label = \"p.adj\")<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/i.imgur.com\/ZGngk3S.png\" alt=\"plot of chunk ggpubr-add-adjusted-p-values-to-multi-panel-ggplot\" \/><\/p>\n<pre class=\"r\"><code># Display the p-value significance levels\r\nbxp + stat_pvalue_manual(stat.test, label = \"p.adj.signif\")<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/i.imgur.com\/1W3sZiI.png\" alt=\"plot of chunk ggpubr-add-adjusted-p-values-to-multi-panel-ggplot\" \/><\/p>\n<pre class=\"r\"><code># Hide ns and change the bracket tip length\r\nbxp + stat_pvalue_manual(\r\n  stat.test, label = \"p.adj.signif\",\r\n  hide.ns = TRUE, tip.length = 0\r\n  )<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/i.imgur.com\/QeusaHv.png\" alt=\"plot of chunk ggpubr-add-adjusted-p-values-to-multi-panel-ggplot\" \/><\/p>\n<pre class=\"r\"><code># Show p-values and significance levels\r\nbxp + stat_pvalue_manual(\r\n  stat.test, label = \"{p.adj}{p.adj.signif}\",\r\n  hide.ns = TRUE, tip.length = 0\r\n  )<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/i.imgur.com\/yOaCK2v.png\" alt=\"plot of chunk ggpubr-add-adjusted-p-values-to-multi-panel-ggplot\" \/><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p># Load required R packages library(ggpubr) library(rstatix) # Data preparation df &lt;- tibble::tribble( ~sample_type, ~expression, ~cancer_type, ~gene, &#8220;cancer&#8221;, 25.8, &#8220;Lung&#8221;, &#8220;Gene1&#8221;, &#8220;cancer&#8221;, 25.5, &#8220;Liver&#8221;, &#8220;Gene1&#8221;, &#8220;cancer&#8221;, 22.4, &#8220;Liver&#8221;, &#8220;Gene1&#8221;, &#8220;cancer&#8221;, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":15705,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"rating_form_position":"","rating_results_position":"","mr_structured_data_type":"","footnotes":""},"categories":[341],"tags":[343],"class_list":["post-15704","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-faq","tag-ggpubr"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>GGPUBR: How to Add Adjusted P-values to a Multi-Panel GGPlot - Datanovia<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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