anchor.diff:        initFilter();
   
         <%-- lets rumble --%>
  -      filterAndDrawChart();
  +      google.load("visualization", "1", {"packages":["corechart"], "callback":filterAndDrawChart});
       })();
   
       <%-- get the browser window size --%>
  
positive.code: 
          var chart = new google.visualization.BarChart(document.getElementById("gene-expression-atlas-chart"));
          chart.draw(data, options);
          
          // attach the hAxis as it does not work natively
          jQuery('<span/>', {
          	text: 't-statistic'
          }).appendTo('#gene-expression-atlas-chart');
        }
      }
  
negative.code:       geneExpressionAtlasDisplayer.peaks.global =
        (geneExpressionAtlasDisplayer.peaks.up > Math.abs(geneExpressionAtlasDisplayer.peaks.down)) ?
        geneExpressionAtlasDisplayer.peaks.up : Math.abs(geneExpressionAtlasDisplayer.peaks.down);
       })();
    </script>
  
    <%-- sidebar --%>
    <div class="sidebar">
    <div class="collection-of-collections">
      <div class="header">
        <div class="switchers">
          <a href="#" title="key" class="active">Key</a> <a href="#" title="controls">Controls</a> <a href="#" title="halp">Help</a>
        </div>
      </div>
      <div class="pane key">
      <div class="legend">
         <strong>Expression</strong>
         <ul class="expression">
           <li><span class="up"></span> Upregulation</li>
           <li><span class="down"></span> Downregulation</li>
           <li><span class="confidence"></span> Low confidence</li>
         </ul>
       </div>
      </div>
      <div class="pane controls" style="display:none;">
        <div class="settings">
          <strong>Sort</strong>
          <ul class="sort">
            <li title="byName">By tissue name</li>
            <li class="active" title="byTStatistic">By t-statistic</li>
            <li title="byPValue">By p-value</li>
          </ul>
  
          <strong>1) Show regulation type</strong>
          <fieldset class="regulation-type">
            <label for="upregulation-check">Upregulation:</label>
            <input type="checkbox" id="upregulation-check" title="UP" checked="checked" autocomplete="off" />
            <label for="downregulation-check">Downregulation:</label>
            <input type="checkbox" id="downregulation-check" title="DOWN" checked="checked" autocomplete="off" />
          </fieldset>
  
        <script type="text/javascript">
          geneExpressionAtlasDisplayer.dragdealers = {};
        </script>
          <strong>2) Adjust the p-value**</strong>
          <fieldset class="p-value">
            <tiles:insert name="geneExpressionAtlasDisplayerNonLinearSlider.jsp">
              <tiles:put name="sliderIdentifier" value="pValue" />
              <tiles:put name="defaultValue" value="${defaultPValue}" />
            </tiles:insert>
          </fieldset>
  
          <strong>3) Adjust the t-statistic*</strong>
          <fieldset class="t-statistic">
            <tiles:insert name="geneExpressionAtlasDisplayerLinearSlider.jsp">
              <tiles:put name="sliderIdentifier" value="tStatistic" />
              <tiles:put name="defaultValue" value="${defaultTValue}" />
            </tiles:insert>
          </fieldset>
  
          <strong>4)</strong>
          <input class="update inactive" type="button" value="Update" title="Update the chart"></input>
        </div>
  
        <input class="toggle-table" type="button" value="Toggle table">
      </div>
      <div class="pane halp" style="display:none;">
        <div class="description">
          <%--<div class="content">--%>
            <%--<div class="overlay"></div>--%>
            <h4>* Moderated t-statistic</h4>
            <p class="small">The basic statistic used for significance analysis is the moderated
          t-statistic, which is computed for each probe and for each contrast.
          This has the same interpretation as an ordinary t-statistic except
          that the standard errors have been moderated across genes, i.e.,
          shrunk towards a common value, using a simple Bayesian model. This has
          the effect of borrowing information from the ensemble of genes to aid
          with inference about each individual gene.<br />
          The moderated t-statistic (t) is the ratio of the log fold change to
          its standard error.</p>
  
          <h4>** p-value</h4>
          <p class="small">The p-value (p-value) is obtained from the moderated t-statistic,
          usually after adjustment for multiple testing: "fdr" which is
          Benjamini and Hochberg's method to control the false discovery rate.</p>
        <%--</div>--%>
        <%--<div class="wrap"><a class="more">Read more</a></div>--%>
      </div>
      </div>
    </div>
    </div>
  
    <script type="text/javascript">
      <%-- call me to draw me --%>
      function drawChart(liszt, redraw) {
        if (liszt.length > 0) {
          googleChart();
        } else {
          notify('Nothing to show, adjust the p-value and/or t-stat to see upto ' + geneExpressionAtlasDisplayer.originalList.byName.length + ' results', true);
        }
  