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diff --git a/web/tutorial/ppt/WebQTLDemo_files/slide0040.htm b/web/tutorial/ppt/WebQTLDemo_files/slide0040.htm new file mode 100755 index 00000000..a71d67b3 --- /dev/null +++ b/web/tutorial/ppt/WebQTLDemo_files/slide0040.htm @@ -0,0 +1,111 @@ +<html>
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<title>PowerPoint Presentation - Complex trait analysis, develop-ment, and
genomics</title>
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href=WebQTLDemo.ppt>
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<meta name=Description content=Jun-19-03>
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<div style='mso-special-format:nobullet;text-align:left;font-family:"Gill Sans";
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348;mso-text-indent-alt:56;mso-line-spacing:" 0 ";mso-margin-left-alt:348;
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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mso-text-raise:0%'><script> + mytop = 0 * g_height; myleft = 0 * g_width; myheight = 0.04 * g_height; mywidth = 0.24 * g_width; + document.write( '<layer top=' + mytop + ' left=' + myleft + ' height=' + myheight + ' width=' + mywidth + ' >' ); +</script><span
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> + mytop = 0.04 * g_height; myleft = 0 * g_width; myheight = 0.03 * g_height; mywidth = 0.25 * g_width; + document.write( '<layer top=' + mytop + ' left=' + myleft + ' height=' + myheight + ' width=' + mywidth + ' >' ); +</script><span
style='text-align:left'><span style='font-size:133%;color:#E9EB5D;mso-color-index:
3'><b>many transcripts </b></span></span></layer><script> + mytop = 0.07 * g_height; myleft = 0 * g_width; myheight = 0.03 * g_height; mywidth = 0.26 * g_width; + document.write( '<layer top=' + mytop + ' left=' + myleft + ' height=' + myheight + ' width=' + mywidth + ' >' ); +</script><span
style='text-align:left'><span style='font-size:133%;color:#E9EB5D;mso-color-index:
3'><b>have correlations </b></span></span></layer><script> + mytop = 0.11 * g_height; myleft = 0 * g_width; myheight = 0.03 * g_height; mywidth = 0.25 * g_width; + document.write( '<layer top=' + mytop + ' left=' + myleft + ' height=' + myheight + ' width=' + mywidth + ' >' ); +</script><span
style='text-align:left'><span style='font-size:133%;color:#E9EB5D;mso-color-index:
3'><b>>0.7? What does </b></span></span></layer><script> + mytop = 0.14 * g_height; myleft = 0 * g_width; myheight = 0.03 * g_height; mywidth = 0.22 * g_width; + document.write( '<layer top=' + mytop + ' left=' + myleft + ' height=' + myheight + ' width=' + mywidth + ' >' ); +</script><span
style='text-align:left'><span style='font-size:133%;color:#E9EB5D;mso-color-index:
3'><b>this imply.</b></span></span></layer></div>
</layer></div>
</LAYER>
+
<layer>
<div id=NotesObj style='display:none'>
<table style='color:white' border=0 width="100%">
<tr>
<td width=5 nowrap></td>
<td width="100%"></td>
</tr>
<tr>
<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"> </span>of tests (12422 tests).</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>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 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>
</td>
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</table>
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