title: How to change loadings.label in PCA plot using ggplot2?
body: <p>I am plotting a PCA analysis in <code>ggplot2</code> and <code>loadings.label</code> overlap with the arrows. I want to move the labels a little to make more accessible the reading of the plot, but I can't find a way to do it. I am attaching the plot below.
  here is part of the data:</p>
  <pre><code>Linfoprolif CORT Testo  FDL Ac.GRO ifn.g il.4 Profile
  1        23.76 0.27  0.96 2.41      6   307   69       1
  2           NA 2.59  0.07 0.39      4   117   58        
  3        25.53 0.16  0.71 2.17      5   273   54       1
  4        31.67 0.88  0.07 0.55      5   211   48       1
  5         6.15 0.24  0.23 1.07      5   224   48       1
  6        26.19 0.74  0.04 0.60      4   308   59       1
  7        10.31 0.34  0.75 2.29      7   295   49       1
  8        22.30 0.42  0.07 0.63      5   271   52       1
  9        24.74 0.29  1.18 2.91      4   236   56       1
  10        9.51 2.19  0.07 0.40      5    54   62       2
  11       22.59 0.19  0.40 3.28      4   272   58       1
  12       22.01 0.28  0.04 0.54      4    67   64       1
  13       39.21 0.21  0.82 1.91      4   235   56       1
  14       42.07 0.32  0.16 0.70      5   362   54       3
  15       13.45 0.30  0.24 2.21      6   146   68       1
  16       15.08 2.19  0.08 0.34      5    58   63       2
  17       20.48 0.38  1.27 2.40      4   278   52       1
  18       12.10 0.83  0.11 0.53      2   146   41       1
  19       61.56 0.07  0.09 1.09      9   305   52       3
  20       35.06 0.59  0.05 0.67      4   220   54       1
  21       33.48 0.68  0.99 1.24      3   102   58       1
  22       20.56 0.94  0.06 1.71      3    58   45       2
  23       26.46 0.12  0.29 1.60      3   210   55       1
  24       24.91 0.56  0.11 0.55      5   108   56       1
  25       29.22 0.42  2.60 1.55      3    84   69       1
  26       19.30 1.63  0.02 0.78      3    62   69       2
  27       14.45 0.22  0.79 1.89      4   245   59       1
  28       20.89 0.72  0.04 0.57      4    85   53       1
  29       26.70 0.36  1.02 2.05      3   309   45       1
  30       27.83 2.66  0.04 0.54      3    52   65       2
  31       34.70 0.46  0.83 1.39      5   120   65       1
  </code></pre>
  <p>and the code</p>
  <pre><code>library(ggfortify)
  p_pca&lt;-d_e_b[c(1,2,3,4,5,6,7)]
  
  p_pca&lt;-na.omit(p_pca)
  pca_res &lt;- prcomp(p_pca, scale. = TRUE)
  
  
  pca_b&lt;-autoplot(pca_res, data = d_e_b, colour = &quot;Profile&quot;,
                  loadings = TRUE, loadings.colour = 'gray30',loadings.size = 5,
                  loadings.label = TRUE, loadings.label.color='black',
                  loadings.label.size = 4) + theme_classic()+
    scale_colour_discrete(&quot;Profile&quot;)+
    theme(text = element_text(size = 20 ),
          axis.line.x = element_line(color=&quot;black&quot;, size = 1),
          axis.line.y = element_line(color=&quot;black&quot;, size = 1),
          axis.text.x=element_text(colour=&quot;black&quot;,angle = 360,vjust = 0.6),
          axis.text.y=element_text(colour=&quot;black&quot;))
  pca_b
  </code></pre>
  <p>Any ideas on how to solve it?</p>
  <p><a href="https://i.stack.imgur.com/HZWiD.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/HZWiD.png" alt="PCA plot" /></a></p>