Pgx Drug Discovery I Flashcards
Null Hypothesis
no association between any allele and drug resistance
P > 0.1
no presumption against the null hypothesis (no significant association)
0.05 < P < 0.1
low presumption against the null hypothesis (marginal association)
P < 0.05
strong presumption against the null hypothesis (significant association)
P < 0.01
very strong presumption against the null hypothesis (very significant association)
Does the p value measure the strength of association of relationship?
NO
- affected by sample size or allele frequency
Measure of the strength
Odds Ratio
Odds Ratio
increased risk for a phenotype by carrying a specific genotype/allele compared to patients without carrying
Odds Ratio Equation
odds of phenotype in an individual with genotype / odds of genotype in an individual without genotype
OR = 1
no association
OR > 1
potentially increases the risk
the higher the OR is, the higher risk the allele will confer to phenotype
OR < 1
potentially decreases the risk
the smaller the OR is, the lower risk the allele will confer to phenotype
95% Confidence Interval
- statistical probability for the odds ratio (standard of error of OR)
95% CI > 1
significant risk effect
95% CI includes 1
no statistical significance
95% CI < 1
significant protective effect
Correction for P Values
- due to a large number of tests for many SNP’s vs the single phenotype, there is a much higher probability to have many SNPs associated with the phenotype just by chance –> multiple testing
- the more SNPs tested, the higher probability for a false positive
Solution for false positive
Bonferroni corretion:
- corrected P = 0.05 / N
IN GENERAL WE USE 5x10^-8 AS CORRECTED SIGNIFICANT GWAS P VALUE
Experiments to Test Hypothesis
CONTROL IS THE KEY (positive & negative control)
Requirements:
1. Sham (negative control)
2. Standard of Care Drug (positive control)
3. Investigational Drug (experiment group)
LARGE SAMPLE SIZE IS ESSENTIAL
CLINICAL STUDY OFTEN USES MEDIAN BUT NOT MEAN
TEST ONE CONCEPT IN MULTIPLE BIOLOGICAL SYSTEMS (molecular, cellular, rodents, human iPSC) TO MAKE RESULTS MORE RELIABLE
What type of distribution do most studies follow?
normal (guassian) distribution (bell curve)
Why do we use the MEDIAN and not the mean?
faster
patient data may not be normally distributed (skewness)