FS 160 Lecture Notes - Lecture 11: Semi-Continuity, Genotyping, Zygosity
FS 160 – Lecture 11 – Probabilistic Genotyping
I. Mixture Interpretation
a. Two parts
i. Determination of alleles present in evidence and deconvolution of mixture
components where possible
1. deconvolution: simplification of a complex signal by removal of
noise
2. Often through comparison to victim and suspect profiles
ii. Providing some kind of statistical answer regarding the weight of the
evidence
1. Multiple approaches and philosophies
b. Statistical approaches
i. Exclusionary approach
1. Random Man Not Excluded (RMNE):
probability that a random person (unrelated individual) would be
included/excluded as contributor to observed DNA mixture
2. Wastes information that should be utlized
3. Completely invalid for complicated mixtures
4. Is only conservative for guilty suspects
a. Advantages
i. Does not require an assumption of the number of
contributors to a mixture
ii. Easier to explain in court
iii. Deconvolution is not necessary
b. Disadvantages
i. Weaker use of available information
1. Robs evidence of its true probative power
because this approach does not consider
suspect’s genotype
ii. Alleles below stochastic threshold cannot be used
for statistical purpose
iii. Potential to include a non-contributor
5. Combined Probability of Inclusion (CPI)
a. CPI = [f(a) + f(b) + f(c) + F(d)]2
b. CPI = (PIM1)(PIM2)
c. When data is below ST, not applicable
6. Combined Probability of Exclusion (CPE)
a. CPE = 1 - CPI
ii. Inferred genotype approach
1. Random Match Probability (RMP): major and minor components
can be successfully separated
into individual profiles
a. Calculated on the evidence as if the component was from
a single source sample
b. RMPminor = 2pq = 2[f(b)][f(c)]
i. Where q is any other allele
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