code: def slamdunkPCAPlot (self):
          
  
          pconfig = {
              'id': 'slamdunk_pca',
              'title': 'Slamdunk: PCA',
              'xlab': 'PC1',
              'ylab': 'PC2',
              'tt_label': 'PC1 {point.x:.2f}: PC2 {point.y:.2f}'
          }
  
          self.add_section (
              name = 'PCA (T&gt;C based)',
              anchor = 'slamdunk_PCA',
              description = """This plot shows the principal components of samples based
                          on the distribution of reads with T&gt;C conversions within UTRs
                          (see the <a href="http://t-neumann.github.io/slamdunk/docs.html#summary" target="_blank">slamdunk docs</a>).""",
              plot = scatter.plot(self.PCA_data, pconfig)
          )
docs: Generate the PCA plots