From ea46f42ee640928b92947bfb204c41a482d80937 Mon Sep 17 00:00:00 2001
From: root
Date: Tue, 8 May 2012 18:39:56 -0500
Subject: Add all the source codes into the github.
---
web/tutorial/ppt/WebQTLDemo_files/slide0040.htm | 111 ++++++++++++++++++++++++
1 file changed, 111 insertions(+)
create mode 100755 web/tutorial/ppt/WebQTLDemo_files/slide0040.htm
(limited to 'web/tutorial/ppt/WebQTLDemo_files/slide0040.htm')
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 @@
+
PowerPoint Presentation - Complex trait analysis, develop-ment, and
genomics
+
lThe App transcript neighborhood
Question: How many transcripts have correlations >0.7? What does this imply.
+
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 numbersof tests (12422 tests).
What does this imply?
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.