code: def regression(args):
      
      p = OptionParser(regression.__doc__)
      opts, args, iopts = p.set_image_options(args, figsize="8x8")
  
      if len(args) != 1:
          sys.exit(not p.print_help())
  
      tsvfile, = args
      df = pd.read_csv(tsvfile, sep="\t")
      chrono = "Chronological age (yr)"
      pred = "Predicted age (yr)"
      resdf = pd.DataFrame({chrono: df["hli_calc_age_sample_taken"], pred: df["Predicted Age"]})
      g = sns.jointplot(chrono, pred, resdf, joint_kws={"s": 6},
                        xlim=(0, 100), ylim=(0, 80))
      g.fig.set_figwidth(iopts.w)
      g.fig.set_figheight(iopts.h)
      outfile = tsvfile.rsplit(".", 1)[0] + ".regression.pdf"
      savefig(outfile)
docs: %prog regression postgenomic-s.tsv
  
      Plot chronological vs. predicted age.