Statistical Interpretation of DNA results Flashcards
What is the prosecutor’s fallacy?
When the prosecutor argues that if the accused were guilty, the probability of the evidence at hand (i.e., DNA match) would be high, therefore given the evidence at hand, the probability of the accused’s guilt must be high.
What is the defendant’s fallacy?
The defendant would state the following: “This crime occurred in a city of 800,000 people. This blood type would be found in approximately 8,000 people. The evidence has provided a probability of 1 in 8,000 that the defendant is guilty and thus has no relevance.”
Why can’t we say that the evidence has a 100% match for the accused?
We did not type the whole genome of the sample to be certain that the evidence belongs to the accused.
What is a conservative estimate?
- deliberately chosen to be more favorable to the defendant than the best (unbiased) estimate would be.
- the match probabilities calculated from reference database.
~database are sampled from a larger population
~ another database from the same population might yield slightly different match probabilities
Report on the most conservative MP (figure in which DNA profile frequency is most abundant)
~The figure compensates for any variation in the MP that another database may deliver.
Outcomes: DNA Test
-Exclusion
DNA match can be excluded even when all loci but one doesn’t match.
Second Law of Probability
Calculating the probability of either one of two events occurring is as simple as adding the probability of each event and then subtracting the probability of both of the events occurring.
P(A or B) = P(A) + P(B) - P(A and B) [1= event occurred, 0= event did not occur]
-We must subtract P(A and B) to avoid double counting
Third Law of Probability (Product Rule): DNA Profile
The probability of two independent events occurring together can be calculated by multiplying the individual probabilities of each event occurring alone.
Match Probability (pM)/ Probability of Identity (PI)
the probability of observing a random match between two unrelated individuals.
- Formula: pM = 1/x
~ x = genotype frequency for a DNA marker (locus)/full profile.
~The probability that two individuals selected at random will have an identical genotype at the tested locus
-Sum of the square of the genotype frequencies.
Likelihood Ratio (LR)
-The probability under one hypothesis that the suspect profile and the evidence-sample profile will both be x, divided by the corresponding probability under hypothesis (2).
~The greater the likelihood ratio, the stronger is the evidence in favor of the hypothesis corresponding to the numerator, that the source of the evidence—sample DNA—and the suspect are the same person.
ODDS form of the Bayes Theorem
the probability that the event will occur divided by the probability that the event will not occur
- Posterior Odds (Judges decision) = Likelihood Ratio (The evidence) x Prior Odds (Court’s evidence)
-Its a valuable means to assess the weight of the evidence
-links the probabilities of the proposition of DNA evidence after the evidence ( posterior odds) to probabilities of the proposition prior to evidences (prior odds)
How do you draw up a population database?
- Convenience Sample: using samples that are convenient (i.e., fellow colleagues)
- Anonymous unlinked: replace personal info w/ number or value.
- Size: 100 samples are more than enough to be reliable and representative of the region’s population.
- Minimum allele frequencies: alleles with low frequency, meaning they occur less than five times in a population
database. - Genetic data analysis tests
How to create a population database?
- Decide on the population group and number of samples
- Collect samples
- Analyze the samples
- Summarize DNA types
- Determine allele frequencies (locus)
- Genetic data analysis using Hardy-Weinberg equilibrium (allele independence) and linkage equilibrium (locus independence)
- Estimate the observed DNA profile frequency
Power of Discrimination (PD)
The probability of discriminating two distinct samples selected at random from the population of interest.
Probability of Discrimination
The probability of discriminating between two unrelated individuals.
Binary Model (CPI/ RMNE)
The probability of the evidence given a proposed genotype is assigned as zero (genotype excluded)/ one (genotype included)
CPI: Combined Probability of Inclusion
RMNE: Random Man Not Excluded
What’s needed to conduct statistical calculation of a binary model- in terms of single source results?
- The alleles/genotypes present in a DNA profile
- The population frequency estimates of the alleles/genotypes (Appx A)
- Genetic formulas used to account for substructure
What’s needed to conduct statistical calculation of a binary model- in terms of DNA mixture?
- Genotype frequency—all the possible genotypes—read into the mixture.
- New genotype frequency calculated for each locus= sum of the genotype frequencies (all possible genotypes—read into the mixture)
- Product: newly generated genotype frequencies.
What are the steps needed when calculating relationship testing?
- Two hypothesis/ statements
- Look at the child’s genotype and decide on the formula
- Substitute the child’s genotype in to the formula
Probability statement - Remember denominator = ‘Random individuals’
When to exclude in cases of familial relatioonship?
