mispitools-package: mispitools: Missing Person Identification Tools

In mispitools: Missing Person Identification Tools

mispitools: Missing Person Identification Tools

Description

The mispitools package provides a comprehensive suite of statistical tools for missing person identification, combining both genetic and non-genetic evidence. It enables forensic geneticists and investigators to compute likelihood ratios (LRs), determine optimal decision thresholds, and assess error rates in database searches.

The package implements Bayesian methodology for evaluating evidence in kinship testing, particularly useful in humanitarian contexts such as identifying victims of enforced disappearances or natural disasters.

Simulation Functions

Functions for simulating LR distributions under different hypotheses:

• sim_lr_genetic: Simulate LRs from genetic (DNA) data

• sim_lr_prelim: Simulate LRs from preliminary investigation data

• sim_reference_pop: Simulate a reference population with traits

• sim_poi_prelim: Generate preliminary data for persons of interest

• sim_mp_prelim: Generate preliminary data for missing persons

LR Calculation Functions

Functions for computing likelihood ratios from different types of evidence:

• lr_sex: LR based on biological sex

• lr_age: LR based on age

• lr_hair_color: LR based on hair color

• lr_pigmentation: LR for combined pigmentation traits

• lr_birthdate: LR based on birth date discrepancies

• lr_combine: Combine LRs from independent sources

• lr_to_dataframe: Convert genetic LR simulations to dataframe

Conditional Probability Tables

Functions for computing conditional probability tables (CPTs):

• cpt_population: CPT based on population frequencies (H2)

• cpt_missing_person: CPT conditioned on MP characteristics (H1)

• error_matrix_hair: Create error/confusion matrix for hair color

Visualization Functions

Functions for visualizing results:

• plot_lr_distribution: Plot LR distributions under H1 and H2

• plot_decision_curve: Plot FPR vs FNR for different thresholds

• plot_cpt: Visualize conditional probability tables

Decision Analysis

Functions for determining optimal thresholds and error rates:

• decision_threshold: Compute optimal LR threshold

• threshold_rates: Compute error rates (FPR, FNR, MCC)

Population Genetics

Functions for working with allele frequency databases:

• get_allele_freqs: Retrieve allele frequencies for a population

Interactive Applications

Shiny applications for interactive analysis:

• app_mispitools: Comprehensive analysis application

• app_lr_comparison: LR comparison and ROC analysis

Datasets

The package includes STR allele frequency databases for multiple populations: Argentina, Asia, Austria, BosniaHerz, China, Europe, Japan, USA.

Core Dependencies

The genetic simulation functionality relies on the forrel and pedtools packages for pedigree handling and likelihood calculations.

Author(s)

Maintainer: Franco Marsico [e-mail] (ORCID)

Authors:

• Suisei Nakagawa [e-mail]

References

Marsico FL, Iudica CE, Herrera Pinero F, et al. (2023). "Likelihood ratios for non-genetic evidence in missing person cases." Forensic Science International: Genetics, 66, 102891. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.fsigen.2023.102891")}

Marsico FL, Vigeland MD, Egeland T, Herrera Pinero F (2021). "Making decisions in missing person identification cases with low statistical power." Forensic Science International: Genetics, 52, 102519. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.fsigen.2021.102519")}

See Also

Useful links:

• https://github.com/MarsicoFL/mispitools

• Report bugs at https://github.com/MarsicoFL/mispitools/issues

mispitools documentation built on Aug. 26, 2026, 1:08 a.m.