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authorZachary Sloan2012-09-19 17:06:42 -0500
committerZachary Sloan2012-09-19 17:06:42 -0500
commit1e081d88b96660c69d2de9e6b00a54f800348cde (patch)
tree32e515376a0103a15c2103a84fd60717c3aeae3f /wqflask/base/webqtlTrait.py
parent6e89a31cf7e654fb1b99d6fa86e7cdabb68cb243 (diff)
downloadgenenetwork2-1e081d88b96660c69d2de9e6b00a54f800348cde.tar.gz
Made pearson/spearman options disappear if lit correlation is chosen, began to address how to deal with Trait object in CorrelationPage
Diffstat (limited to 'wqflask/base/webqtlTrait.py')
-rwxr-xr-xwqflask/base/webqtlTrait.py34
1 files changed, 34 insertions, 0 deletions
diff --git a/wqflask/base/webqtlTrait.py b/wqflask/base/webqtlTrait.py
index 337493ef..8240eafc 100755
--- a/wqflask/base/webqtlTrait.py
+++ b/wqflask/base/webqtlTrait.py
@@ -660,3 +660,37 @@ class webqtlTrait:
else:
return dict(name = self.db.fullname,
url = webqtlConfig.INFOPAGEHREF % self.db.name)
+
+ def calculate_correlation(self, values, method):
+ """Calculate the correlation value and p value according to the method specified"""
+
+ #ZS: This takes the list of values of the trait our selected trait is being correlated against and removes the values of the samples our trait has no value for
+ #There's probably a better way of dealing with this, but I'll have to ask Christian
+ updated_raw_values = []
+ updated_values = []
+ for i in range(len(values)):
+ if values[i] != "None":
+ updated_raw_values.append(self.raw_values[i])
+ updated_values.append(values[i])
+
+ self.raw_values = updated_raw_values
+ values = updated_values
+
+ if method == METHOD_SAMPLE_PEARSON or method == METHOD_LIT or method == METHOD_TISSUE_PEARSON:
+ corr, nOverlap = webqtlUtil.calCorrelation(self.raw_values, values, len(values))
+ else:
+ corr, nOverlap = webqtlUtil.calCorrelationRank(self.raw_values, values, len(values))
+
+ self.correlation = corr
+ self.overlap = nOverlap
+
+ if self.overlap < 3:
+ self.p_value = 1.0
+ else:
+ #ZS - This is probably the wrong way to deal with this. Correlation values of 1.0 definitely exist (the trait correlated against itself), so zero division needs to br prevented.
+ if abs(self.correlation) >= 1.0:
+ self.p_value = 0.0
+ else:
+ ZValue = 0.5*log((1.0+self.correlation)/(1.0-self.correlation))
+ ZValue = ZValue*sqrt(self.overlap-3)
+ self.p_value = 2.0*(1.0 - reaper.normp(abs(ZValue)))