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Solving the Arizona search problem by imputation.

ABSTRACT: An "Arizona search" is an evaluation of the numbers of pairs of profiles in a forensic-genetic database that possess partial or complete genotypic matches; such a search assists in establishing the extent to which a set of loci provides unique identifications. In forensic genetics, however, the potential for performing Arizona searches is constrained by the limited availability of actual forensic profiles for research purposes. Here, we use genotype imputation to circumvent this problem. From a database of genomes, we impute genotypes of forensic short-tandem-repeat (STR) loci from neighboring single-nucleotide polymorphisms (SNPs), searching for partial STR matches using the imputed profiles. We compare the distributions of the numbers of partial matches in imputed and actual profiles, finding close agreement. Despite limited potential for performing Arizona searches with actual forensic STR profiles, the questions that such searches seek to answer can be posed with imputation-based Arizona searches in increasingly large SNP databases.

SUBMITTER: Lappo E

PROVIDER: S-EPMC10845060 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Solving the Arizona search problem by imputation.

Lappo Egor E Rosenberg Noah A NA

iScience 20240112 2

An "Arizona search" is an evaluation of the numbers of pairs of profiles in a forensic-genetic database that possess partial or complete genotypic matches; such a search assists in establishing the extent to which a set of loci provides unique identifications. In forensic genetics, however, the potential for performing Arizona searches is constrained by the limited availability of actual forensic profiles for research purposes. Here, we use genotype imputation to circumvent this problem. From a ...[more]

PMID: 38323008

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Project description:In this paper we argue that a synthesis of findings across the various sub-areas of research in complex problem solving and consequently progress in theory building is hampered by an insufficient differentiation of complexity and difficulty. In the proposed framework of person, task, and situation (PTS), complexity is conceptualized as a quality that is determined by the cognitive demands that the characteristics of the task and the situation impose. Difficulty represents the quantifiable level of a person's success in dealing with such demands. We use the well-documented "semantic effect" as an exemplar for testing some of the conceptual assumptions derived from the PTS framework. We demonstrate how a differentiation between complexity and difficulty can help take beyond a potentially too narrowly defined psychometric perspective and subsequently gain a better understanding of the cognitive mechanisms behind this effect. In an empirical study a total of 240 university students were randomly allocated to one of four conditions. The four conditions resulted from contrasting the semanticity level of the variable labels used in the CPS system (high vs. low) and two instruction conditions for how to explore the CPS system's causal structure (starting with the assumption that all relationships between variables existed vs. starting with the assumption that none of the relationships existed). The variation in the instruction aimed at inducing knowledge acquisition processes of either (1) systematic elimination of presumptions, or (2) systematic compilation of a mental representation of the causal structure underpinning the system. Results indicate that (a) it is more complex to adopt a "blank slate" perspective under high semanticity as it requires processes of inhibiting prior assumptions, and (b) it seems more difficult to employ a systematic heuristic when testing against presumptions. In combination, situational characteristics, such as the semanticity of variable labels, have the potential to trigger qualitatively different tasks. Failing to differentiate between 'task' and 'situation' as independent sources of complexity and treating complexity and difficulty synonymously threaten the validity of performance scores obtained in CPS research.

Dataset Information

Solving the Arizona search problem by imputation.

Publications

Solving the Arizona search problem by imputation.

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