text: #!/usr/bin/env python
  # Copyright (C) 2018 Emanuel Goncalves
  
  import crispy as cy
  import matplotlib.pyplot as plt
  from analysis.DataImporter import DataImporter
  
  if __name__ == '__main__':
      # - Crispy bed files
      data = DataImporter()
  
      samples = ['HCC1954', 'NCI-H2087']
  
      beds = data.get_crispy_beds(subset=samples)
      cnvs = data.get_copy_number()
  
      # - Chromosome plots
      chrs_to_plot = [
          ('HCC1954', 'chr8', (100, 145), ['MYC']),
          ('NCI-H2087', 'chr8', (100, 145), ['MYC'])
      ]
  
      for s, chrm, xlim, genes in chrs_to_plot:
          crispy_bed, ascat_bed = beds[s], cnvs.query(f"sample == '{s}'")
  
          ax = cy.QCplot.plot_chromosome(crispy_bed, ascat_bed, chrm, legend=True, highlight=genes)
  
          if xlim is not None:
              ax.set_xlim(xlim)
  
          ax.set_title(s)
          ax.set_xlabel(f'Position on chromosome {chrm} (Mb)')
  
          plt.gcf().set_size_inches(3, 2)
          plt.savefig(f'reports/analysis/chromosome_plot_{s}_{chrm}.pdf', bbox_inches='tight', transparent=True)
          plt.close('all')
  