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56;position:absolute;top:0%;left:2.11%;width:96.46%;height:50.6%'><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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height:18.72%'><span style='position:absolute;top:0%;left:0%;width:91.91%'><span
style='font-size:150%;color:#E9EB5D;mso-color-index:3'><b>Question: </b></span><span
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style='position:absolute;top:21.69%;left:0%;width:97.47%'><span
style='font-size:133%;color:#E9EB5D;mso-color-index:3'><b>many transcripts </b></span></span><span
style='position:absolute;top:40.56%;left:0%;width:100.0%'><span
style='font-size:133%;color:#E9EB5D;mso-color-index:3'><b>have correlations </b></span></span><span
style='position:absolute;top:59.43%;left:0%;width:97.97%'><span
style='font-size:133%;color:#E9EB5D;mso-color-index:3'><b>>0.7? What does </b></span></span><span
style='position:absolute;top:79.24%;left:0%;width:85.35%'><span
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<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">
</span>of tests (12422 tests).</font><br>
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<td align=left colspan=1><font face=Helvetica size=3>What does this imply?</font><br>
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<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 ÒindependentÓ test we
effectively are performing when we use array data in this way. Are we testing
12000 independent transcripts or just 1200 transcriptional ÒmodulesÓ 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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