web/tutorial/ppt/WebQTLDemo_files/slide0040.htm


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<title>PowerPoint Presentation  -  Complex trait analysis, develop-ment, and
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mso-text-indent-alt:56'><span style='mso-special-format:nobullet;display:none;
color:#FBFDB8;font-family:"Monotype Sorts";font-size:99%'>l</span><span
style='font-size:106%;color:#E9EB5D;mso-color-index:3'>The </span><span
style='font-size:106%;color:#E9EB5D;mso-color-index:3'><i>App</i></span><span
style='font-size:106%;color:#E9EB5D;mso-color-index:3'> transcript neighborhood</span></div>

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style='text-align:left'><span style='font-size:150%;color:#E9EB5D;mso-color-index:
3'><b>Question: </b></span><span style='font-size:133%;color:#E9EB5D;
mso-color-index:3'><b>How </b></span></span></layer><script>
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3'><b>many transcripts </b></span></span></layer><script>
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3'><b>have correlations </b></span></span></layer><script>
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3'><b>&gt;0.7? What does </b></span></span></layer><script>
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style='text-align:left'><span style='font-size:133%;color:#E9EB5D;mso-color-index:
3'><b>this imply.</b></span></span></layer></div>

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 <div id=NotesObj style='display:none'>
 <table style='color:white' border=0 width="100%">
  <tr>
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   <td colspan=1></td>
   <td align=left colspan=1><font face=Helvetica size=3>The answer is a strong
   Yes. A very large number of transcripts have correlations above 0.7
   (absolute value) with App mRNA. The precise number today is 208. But this
   will change as we add more strains and arrays. In any case, this is a fairly
   large number and all of these correlations are significant at alpha .05 even
   when correcting for the enormous numbers<span style="mso-spacerun:
   yes">&nbsp; </span>of tests (12422 tests).</font><br>
   </td>
  </tr>
  <tr>
   <td colspan=1></td>
   <td align=left colspan=1><br>
   </td>
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  <tr>
   <td colspan=1></td>
   <td align=left colspan=1><font face=Helvetica size=3>What does this imply?</font><br>
   </td>
  </tr>
  <tr>
   <td colspan=1></td>
   <td align=left colspan=1><br>
   </td>
  </tr>
  <tr>
   <td colspan=1></td>
   <td align=left colspan=1><font face=Helvetica size=3>That there can be
   massive codependence of expression variance among transcripts. App is NOT an
   isolated instance. This is improtant biologically and statistically. From a
   statistical perspective, we would like to know how many �independent� test
   we effectively are performing when we use array data in this way. Are we
   testing 12000 independent transcripts or just 1200 transcriptional �modules�
   each with blurred boarders but each with about 10 effective members. There
   is no answer yet, but we probaby have a large enough data set to begin to
   answer this question.</font><br>
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