text: user6827: I have generated a volcano plot with a differential expression file.
  Code for inputing file:
  macrophage_list <- read.table("differential_expression_macrophage.csv", header = T, sep = ",")
  library(tidyr)
  final_df <- df %>% pivot_longer(., -c(Feature.ID, Feature.Name), names_to = c("set",".value"), names_pattern = "(.+)_(.+)")
  
  # A tibble: 80 x 6
     Feature.ID Feature.Name set       Mean.Counts Log2.fold.change Adjusted.p.value
     <fct>      <fct>        <chr>           <dbl>            <dbl>            <dbl>
   1 a          A            Cluster.1    0.000961            0.292           1     
   2 a          A            Cluster.2    0.000902            0.793           1     
   3 a          A            Cluster.3    0.00181             1.46            0.758 
   4 a          A            Cluster.4    0.000642            0.269           1     
   5 b          B            Cluster.1    0.000320            1.95            0.910 
   6 b          B            Cluster.2    0.00180             4.77            0.154 
   7 b          B            Cluster.3    0                   2.19            1     
   8 b          B            Cluster.4    0                   1.66            1     
   9 c          C            Cluster.1    0.00128            -2.01            0.0467
  10 c          C            Cluster.2    0.00632             0.352           1     
  # … with 70 more rows
  
  output of head(final_tumor)
  # A tibble: 6 x 6
    Feature.ID        Feature.Name set       Mean.Counts Log2.fold.change Adjusted.p.value
    <fct>             <fct>        <chr>           <dbl>            <dbl>            <dbl>
  1 ENSG00000227232.5 WASH7P       Cluster.1     0                   1.50            1    
  2 ENSG00000227232.5 WASH7P       Cluster.2     0                   1.73            1    
  3 ENSG00000227232.5 WASH7P       Cluster.3     0                   1.77            1    
  4 ENSG00000227232.5 WASH7P       Cluster.4     0.00114             4.30            0.293
  5 ENSG00000227232.5 WASH7P       Cluster.5     0                   2.15            1    
  6 ENSG00000227232.5 WASH7P       Cluster.6     0                   1.22            1 
  
  output of tail(final_tumor)
  # A tibble: 6 x 6
    Feature.ID        Feature.Name set        Mean.Counts Log2.fold.change Adjusted.p.value
    <fct>             <fct>        <chr>            <dbl>            <dbl>            <dbl>
  1 ENSG00000210196.2 MT-TP        Cluster.6       0.0699          -0.202           0.790  
  2 ENSG00000210196.2 MT-TP        Cluster.7       0.0801           0.0386          1      
  3 ENSG00000210196.2 MT-TP        Cluster.8       0.0711           0.0875          1      
  4 ENSG00000210196.2 MT-TP        Cluster.9       0.0152          -2.31            0.00127
  5 ENSG00000210196.2 MT-TP        Cluster.10      0.0147          -2.30            0.00612
  6 ENSG00000210196.2 MT-TP        Cluster.11      0.122            0.762           1  
  
  Code for generating volcano plot:
  library(ggplot2)
  library(ggrepel)
  ggplot(final_tumor, aes(x = Log2.fold.change,y = -log10(Adjusted.p.value), label = Feature.Name))+ 
    geom_point()+
    geom_text_repel(data = subset(final_tumor, Adjusted.p.value < 0.05), 
                    aes(label = Feature.Name))
  
  Now, I want to pull out a certain gene, Casp14, from the list and box it on the plot. How do I do that?
  
  
  user6437: As you did for labeling genes with an adjusted p value below 0.05, you can subset your dataset for keeping only rows corresponding to "Casp14":
  library(ggplot2)
  library(ggrepel)
  ggplot(final_tumor, aes(x = Log2.fold.change,y = -log10(Adjusted.p.value), label = Feature.Name))+ 
    geom_point()+
    geom_text_repel(data = subset(final_tumor, Adjusted.p.value < 0.05), 
                    aes(label = Feature.Name))+
    geom_text_repel(data = subset(final_tumor, Feature.Name == "Casp14"), 
                    aes(label = Feature.Name), color = "red")
  
  With this code, you should see now the labeling of the gene of interest (Casp14) in red on your volcano plot. 
  
original_text: 6827: <p>I have generated a volcano plot with a differential expression file.</p>
  
  <p>Code for inputing file:</p>
  
  <p><code>macrophage_list &lt;- read.table("differential_expression_macrophage.csv", header = T, sep = ",")</code></p>
  
  <pre><code>library(tidyr)
  final_df &lt;- df %&gt;% pivot_longer(., -c(Feature.ID, Feature.Name), names_to = c("set",".value"), names_pattern = "(.+)_(.+)")
  
  # A tibble: 80 x 6
     Feature.ID Feature.Name set       Mean.Counts Log2.fold.change Adjusted.p.value
     &lt;fct&gt;      &lt;fct&gt;        &lt;chr&gt;           &lt;dbl&gt;            &lt;dbl&gt;            &lt;dbl&gt;
   1 a          A            Cluster.1    0.000961            0.292           1     
   2 a          A            Cluster.2    0.000902            0.793           1     
   3 a          A            Cluster.3    0.00181             1.46            0.758 
   4 a          A            Cluster.4    0.000642            0.269           1     
   5 b          B            Cluster.1    0.000320            1.95            0.910 
   6 b          B            Cluster.2    0.00180             4.77            0.154 
   7 b          B            Cluster.3    0                   2.19            1     
   8 b          B            Cluster.4    0                   1.66            1     
   9 c          C            Cluster.1    0.00128            -2.01            0.0467
  10 c          C            Cluster.2    0.00632             0.352           1     
  # … with 70 more rows
  </code></pre>
  
  <p>output of head(final_tumor)</p>
  
  <pre><code># A tibble: 6 x 6
    Feature.ID        Feature.Name set       Mean.Counts Log2.fold.change Adjusted.p.value
    &lt;fct&gt;             &lt;fct&gt;        &lt;chr&gt;           &lt;dbl&gt;            &lt;dbl&gt;            &lt;dbl&gt;
  1 ENSG00000227232.5 WASH7P       Cluster.1     0                   1.50            1    
  2 ENSG00000227232.5 WASH7P       Cluster.2     0                   1.73            1    
  3 ENSG00000227232.5 WASH7P       Cluster.3     0                   1.77            1    
  4 ENSG00000227232.5 WASH7P       Cluster.4     0.00114             4.30            0.293
  5 ENSG00000227232.5 WASH7P       Cluster.5     0                   2.15            1    
  6 ENSG00000227232.5 WASH7P       Cluster.6     0                   1.22            1 
  </code></pre>
  
  <p>output of tail(final_tumor)</p>
  
  <pre><code># A tibble: 6 x 6
    Feature.ID        Feature.Name set        Mean.Counts Log2.fold.change Adjusted.p.value
    &lt;fct&gt;             &lt;fct&gt;        &lt;chr&gt;            &lt;dbl&gt;            &lt;dbl&gt;            &lt;dbl&gt;
  1 ENSG00000210196.2 MT-TP        Cluster.6       0.0699          -0.202           0.790  
  2 ENSG00000210196.2 MT-TP        Cluster.7       0.0801           0.0386          1      
  3 ENSG00000210196.2 MT-TP        Cluster.8       0.0711           0.0875          1      
  4 ENSG00000210196.2 MT-TP        Cluster.9       0.0152          -2.31            0.00127
  5 ENSG00000210196.2 MT-TP        Cluster.10      0.0147          -2.30            0.00612
  6 ENSG00000210196.2 MT-TP        Cluster.11      0.122            0.762           1  
  </code></pre>
  
  <p>Code for generating volcano plot:</p>
  
  <pre><code>library(ggplot2)
  library(ggrepel)
  ggplot(final_tumor, aes(x = Log2.fold.change,y = -log10(Adjusted.p.value), label = Feature.Name))+ 
    geom_point()+
    geom_text_repel(data = subset(final_tumor, Adjusted.p.value &lt; 0.05), 
                    aes(label = Feature.Name))
  </code></pre>
  
  <p>Now, I want to pull out a certain gene, Casp14, from the list and box it on the plot. How do I do that?</p>
  
  <p><a href="https://i.stack.imgur.com/PCi7U.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/PCi7U.png" alt="ggplot of rep_final"></a></p>
   6437: <p>As you did for labeling genes with an adjusted p value below 0.05, you can subset your dataset for keeping only rows corresponding to "Casp14":</p>
  
  <pre class="lang-r prettyprint-override"><code>library(ggplot2)
  library(ggrepel)
  ggplot(final_tumor, aes(x = Log2.fold.change,y = -log10(Adjusted.p.value), label = Feature.Name))+ 
    geom_point()+
    geom_text_repel(data = subset(final_tumor, Adjusted.p.value &lt; 0.05), 
                    aes(label = Feature.Name))+
    geom_text_repel(data = subset(final_tumor, Feature.Name == "Casp14"), 
                    aes(label = Feature.Name), color = "red")
  </code></pre>
  
  <p>With this code, you should see now the labeling of the gene of interest (Casp14) in red on your volcano plot. </p>
  