Mass Identifications: Statistical Methods in Forensic Genetics summarizes the state-of-the-art in the field, including methods and recent development in genetics (sequencing). The book's authors focus on practical applications and implementation, helping readers determine how to approach the problem to identify individuals using DNA and statistically summarize evidence. Written by leading experts in the field for forensic scientists, geneticists, forensic anthropologists, and pathologists working with identifications, the book is ideal for scientists and practitioners in many areas.

Relationship Inference in Familias and R discusses the use of Familias and R software to understand genetic kinship of two or more DNA samples. This software is commonly used for forensic cases to establish paternity, identify victims or analyze genetic evidence at crime scenes when kinship is involved. The book explores utilizing Familias software and R packages for difficult situations including inbred families, mutations and missing data from degraded DNA. The book additionally addresses identification following mass disasters, familial searching, non-autosomal marker analysis and relationship inference using linked markers. The second part of the book focuses on more statistical issues such as estimation and uncertainty of model parameters. Although written for use with human DNA, the principles can be applied to non-human genetics for animal pedigrees and/or analysis of plants for agriculture purposes. The book contains necessary tools to evaluate any type of forensic case where kinship is an issue.