text: user4595: I have this data frame
  
  head(d)
  
  # A tibble: 6 x 3
    gene  variable       value
  1 CCT5  Res_immune     10.6 
  2 CCT5  Non_res_immune 10.5 
  3 CDK1  Res_immune      9.25
  4 CXCL5 Non_res_immune  9.82
  5 GBP1  Res_immune      9.04
  6 GBP1  Non_res_immune  9.43
  > 
  
  And this code
  library(ggplot2)
  library(ggrepel)
  ggplot(d, aes(x = variable, y = value, fill = variable, label = gene))+
    geom_boxplot(alpha = 0.2)+
    geom_point(position = position_jitter(width = 0.2, seed = 2), show.legend = FALSE)+
    geom_text_repel(position = position_jitter(0.2, seed = 2), show.legend = FALSE)
  
  The genes in first column are involved in cytokine signaling pathway in two groups of patients
  This is my plot
  
  I have another data frame for genes in IL17 signaling in the sample patients like
  head(d)
  # A tibble: 6 x 3
    gene  variable       value
    <chr> <chr>          <dbl>
  1 CDK6  Res_immune     17.6 
  2 IL6  Non_res_immune 14.5 
  3 CXCL8  Res_immune      1.25
  
  How I can put plots from both data in a grade like below where the name of pathways shown instead of DEL, INS, SNP and total like below picture?
  
  
  user6437: What you are looking for is facetting. Using this key word on any search engines you will find dozen of answers describing its use: https://ggplot2.tidyverse.org/reference/facet_grid.html and https://ggplot2.tidyverse.org/reference/facet_wrap.html
  To prepare the faceting in ggplot2, a possible way is to bind both dataframes together by first specifying which group they belong such as:
  cytokine$Group = "Cytokine"
  il17$Group = "IL17"
  DF <- rbind(cytokine,il17)
  DF
  
      gene       variable value    Group
  1:  CCT5     Res_immune 10.60 Cytokine
  2:  CCT5 Non_res_immune 10.50 Cytokine
  3:  CDK1     Res_immune  9.25 Cytokine
  4: CXCL5 Non_res_immune  9.82 Cytokine
  5:  GBP1     Res_immune  9.04 Cytokine
  6:  GBP1 Non_res_immune  9.43 Cytokine
  7:  CDK6     Res_immune 17.60     IL17
  8:   IL6 Non_res_immune 14.50     IL17
  9: CXCL8     Res_immune  1.25     IL17
  
  Then, use facet_grid function of ggplot2:
  library(ggplot2)
  library(ggrepel)
  ggplot(DF, aes(x = variable, y = value, fill = variable, label = gene))+
    geom_boxplot(alpha = 0.2)+
    geom_point(position = position_jitter(width = 0.2, seed = 2), show.legend = FALSE)+
    geom_text_repel(position = position_jitter(0.2, seed = 2), show.legend = FALSE)+
    facet_grid(Group~., scales = "free")
  
  
  Alternatively, you can use facet_grid (or facet_wrap) to have your plot in a single row:
  library(ggplot2)
  library(ggrepel)
  ggplot(DF, aes(x = variable, y = value, fill = variable, label = gene))+
    geom_boxplot(alpha = 0.2)+
    geom_point(position = position_jitter(width = 0.2, seed = 2), show.legend = FALSE)+
    geom_text_repel(position = position_jitter(0.2, seed = 2), show.legend = FALSE)+
    facet_wrap(.~Group, scales = "free")
  
  
  Reproducible data example
  structure(list(gene = c("CCT5", "CCT5", "CDK1", "CXCL5", "GBP1", 
  "GBP1"), variable = c("Res_immune", "Non_res_immune", "Res_immune", 
  "Non_res_immune", "Res_immune", "Non_res_immune"), value = c(10.6, 
  10.5, 9.25, 9.82, 9.04, 9.43), Group = c("Cytokine", "Cytokine", 
  "Cytokine", "Cytokine", "Cytokine", "Cytokine")), row.names = c(NA, 
  -6L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x55bfc0db9350>)
  
  and
  structure(list(gene = c("CDK6", "IL6", "CXCL8"), variable = c("Res_immune", 
  "Non_res_immune", "Res_immune"), value = c(17.6, 14.5, 1.25), 
      Group = c("IL17", "IL17", "IL17")), row.names = c(NA, -3L
  ), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x55bfc0db9350>)
  
  
original_text: 4595: <p>I have this data frame</p>
  
  <blockquote>
    <p>head(d)</p>
  </blockquote>
  
  <pre><code># A tibble: 6 x 3
    gene  variable       value
  1 CCT5  Res_immune     10.6 
  2 CCT5  Non_res_immune 10.5 
  3 CDK1  Res_immune      9.25
  4 CXCL5 Non_res_immune  9.82
  5 GBP1  Res_immune      9.04
  6 GBP1  Non_res_immune  9.43
  &gt; 
  </code></pre>
  
  <p>And this code</p>
  
  <pre><code>library(ggplot2)
  library(ggrepel)
  ggplot(d, aes(x = variable, y = value, fill = variable, label = gene))+
    geom_boxplot(alpha = 0.2)+
    geom_point(position = position_jitter(width = 0.2, seed = 2), show.legend = FALSE)+
    geom_text_repel(position = position_jitter(0.2, seed = 2), show.legend = FALSE)
  </code></pre>
  
  <p>The genes in first column are involved in cytokine signaling pathway in two groups of patients</p>
  
  <p>This is my plot
  <a href="https://i.stack.imgur.com/2ciYI.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/2ciYI.png" alt="enter image description here"></a></p>
  
  <p>I have another data frame for genes in IL17 signaling in the sample patients like</p>
  
  <p>head(d)</p>
  
  <pre><code># A tibble: 6 x 3
    gene  variable       value
    &lt;chr&gt; &lt;chr&gt;          &lt;dbl&gt;
  1 CDK6  Res_immune     17.6 
  2 IL6  Non_res_immune 14.5 
  3 CXCL8  Res_immune      1.25
  </code></pre>
  
  <p>How I can put plots from both data in a grade like below where the name of pathways shown instead of DEL, INS, SNP and total like below picture?</p>
  
  <p><img src="https://i.stack.imgur.com/aRH0K.png" alt=""></p>
   6437: <p>What you are looking for is <code>facetting</code>. Using this key word on any search engines you will find dozen of answers describing its use: <a href="https://ggplot2.tidyverse.org/reference/facet_grid.html" rel="nofollow noreferrer">https://ggplot2.tidyverse.org/reference/facet_grid.html</a> and <a href="https://ggplot2.tidyverse.org/reference/facet_wrap.html" rel="nofollow noreferrer">https://ggplot2.tidyverse.org/reference/facet_wrap.html</a></p>
  
  <p>To prepare the faceting in <code>ggplot2</code>, a possible way is to bind both dataframes together by first specifying which group they belong such as:</p>
  
  <pre class="lang-r prettyprint-override"><code>cytokine<span class="math-container">$Group = "Cytokine"
  il17$</span>Group = "IL17"
  DF &lt;- rbind(cytokine,il17)
  DF
  
      gene       variable value    Group
  1:  CCT5     Res_immune 10.60 Cytokine
  2:  CCT5 Non_res_immune 10.50 Cytokine
  3:  CDK1     Res_immune  9.25 Cytokine
  4: CXCL5 Non_res_immune  9.82 Cytokine
  5:  GBP1     Res_immune  9.04 Cytokine
  6:  GBP1 Non_res_immune  9.43 Cytokine
  7:  CDK6     Res_immune 17.60     IL17
  8:   IL6 Non_res_immune 14.50     IL17
  9: CXCL8     Res_immune  1.25     IL17
  </code></pre>
  
  <p>Then, use <code>facet_grid</code> function of <code>ggplot2</code>:</p>
  
  <pre class="lang-r prettyprint-override"><code>library(ggplot2)
  library(ggrepel)
  ggplot(DF, aes(x = variable, y = value, fill = variable, label = gene))+
    geom_boxplot(alpha = 0.2)+
    geom_point(position = position_jitter(width = 0.2, seed = 2), show.legend = FALSE)+
    geom_text_repel(position = position_jitter(0.2, seed = 2), show.legend = FALSE)+
    facet_grid(Group~., scales = "free")
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/P9c3f.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/P9c3f.png" alt="enter image description here"></a></p>
  
  <p>Alternatively, you can use <code>facet_grid</code> (or <code>facet_wrap</code>) to have your plot in a single row:</p>
  
  <pre class="lang-r prettyprint-override"><code>library(ggplot2)
  library(ggrepel)
  ggplot(DF, aes(x = variable, y = value, fill = variable, label = gene))+
    geom_boxplot(alpha = 0.2)+
    geom_point(position = position_jitter(width = 0.2, seed = 2), show.legend = FALSE)+
    geom_text_repel(position = position_jitter(0.2, seed = 2), show.legend = FALSE)+
    facet_wrap(.~Group, scales = "free")
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/AohiU.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/AohiU.png" alt="enter image description here"></a></p>
  
  <p><strong>Reproducible data example</strong></p>
  
  <pre class="lang-r prettyprint-override"><code>structure(list(gene = c("CCT5", "CCT5", "CDK1", "CXCL5", "GBP1", 
  "GBP1"), variable = c("Res_immune", "Non_res_immune", "Res_immune", 
  "Non_res_immune", "Res_immune", "Non_res_immune"), value = c(10.6, 
  10.5, 9.25, 9.82, 9.04, 9.43), Group = c("Cytokine", "Cytokine", 
  "Cytokine", "Cytokine", "Cytokine", "Cytokine")), row.names = c(NA, 
  -6L), class = c("data.table", "data.frame"), .internal.selfref = &lt;pointer: 0x55bfc0db9350&gt;)
  </code></pre>
  
  <p>and</p>
  
  <pre class="lang-r prettyprint-override"><code>structure(list(gene = c("CDK6", "IL6", "CXCL8"), variable = c("Res_immune", 
  "Non_res_immune", "Res_immune"), value = c(17.6, 14.5, 1.25), 
      Group = c("IL17", "IL17", "IL17")), row.names = c(NA, -3L
  ), class = c("data.table", "data.frame"), .internal.selfref = &lt;pointer: 0x55bfc0db9350&gt;)
  </code></pre>
  