Analytical validation stats

gistfile1.txt

# definitions of calculations

# sensitivity is the ability of test to detect the disease when it is present; it is defined as # true positives/# of samples with disease or condition

# specificity is the ability of a test to exclude the disease when it is absent, it is defined as the number of true negatives/# without the disease or condition

# positive predictive value (PPV) - the likelihood that a positive test truly represents the presence of the disease or condition; it is defined as # true positives/# all positives. A test has a high PPV if a large percentage of prople who get a positive test result actually have the disease or condition.

# negative predictive value (NPV) - the likelihood that a negative test truly represents the absence of the disease or condition; it is defined as # true negatives/# all negatives. A test has a high NPV if a large percentage of prople who get a negative test result really don't have the disease or condition.

# how we define the values
# true positives: 
#	def 1: all genes present in more than half of the subsets
#	def 2: all genes present in more 2 of the subsets with more than 10M UMEND reads

# true negatives:
#	def 1 (bad): all genes identified in any samples as up outliers, but not reaching criteria for true positives (~20)
#	def 2 (better): all tested genes (58582) not reaching criteria for true positives (~ 58k)
#	def 3 (unknown): all cancer genes (~500) not reaching criteria for true positive 
#	def 4 (unknown - for pathway enrichment): all pathways not reaching criteria for true positives