ANTH 499: Computational Genetic Genealogy

Beloved African Genetic Genealogy Lab

Explore human lineage and kinship through the power of computational genetic genealogy.

Dr. LaKisha David Assistant Professor Department of Anthropology University of Illinois Urbana-Champaign

Course Information

ANTH 499: Computational Genetic Genealogy

CRN: 65203 Spring 2025

Logistics

  • TR 2:00PM - 3:20PM
  • IGB room 607
  • 4 Credit Hours
  • 01/21/25-05/07/25

About This Course

This course equips students with the computational tools necessary to analyze genetic data and infer family trees, offering an approach to understanding human lineage through genetic genealogy. Students will apply advanced computational methods using Python, Java, and Bash to trace genetic relationships over multiple generations.

The focus on genetic data, particularly within the context of mass human trafficking from Africa, enables students to explore critical anthropological questions about kinship, migration, and human adaptation in the face of historical disruptions. Genetic genealogy represents a focused exploration of recent ancestry (last ~7 generations), providing a refined approach to studying human history and migration patterns. Unlike studies rooted in evolutionary timescales, this method allows us to trace the impact of social, political, and environmental factors on family lineages, enriching anthropological inquiry with a level of precision previously unavailable.

By linking genetic data with genealogical records, students can enhance their understanding of human history in ways that complement archaeological findings and historical documentation taught in other courses. This course prepares students not only for roles in genealogical research, forensic anthropology, and bioinformatics but also for future work in developing the computational tools that drive genetic family tree inference. By mastering these methods, students will be positioned to contribute to the advancement of computational genetics and genealogical research.

Course Themes

This course explores several key thematic areas in computational genetic genealogy through a deep dive into the Bonsai v3 pedigree reconstruction system:

Genetic Foundations

Understanding IBD segments, inheritance patterns, and genetic relationship markers

Statistical Inference

Probabilistic models for relationship inference and confidence assessment

Pedigree Construction

Building, optimizing, and merging family structures from genetic evidence

Algorithmic Efficiency

Performance optimization, caching strategies, and computational techniques

Complex Relationships

Handling special cases like twins, endogamy, and unusual relationship patterns

Visualization

Techniques for rendering and interpreting complex pedigree structures

System Integration

Combining components into comprehensive reconstruction pipelines

Real-World Applications

Applying techniques to practical genetic genealogy challenges and datasets

The course covers these themes across 30 lab sessions exploring the complete Bonsai v3 system. See the Lab Series section below for links to individual labs.

Lab Series

Key Features

Production Code Focus

All labs examine the true Bonsai v3 implementation from the utils directory, not simplified variants.

Interactive Learning

Each lab includes access to an interactive JupyterLite notebook for hands-on experimentation.

Comprehensive Coverage

The curriculum covers all major components and algorithms in the Bonsai v3 system.

Beyond the Code

Each lab explores broader implications and applications of the concepts being covered.

Getting Started

Browser-Based

No installation required! Access interactive Jupyter notebooks directly in your browser via JupyterLite.

Launch JupyterLite

Local Environment

For the full experience, clone the repository and set up your local environment with Python and dependencies.

View on GitHub

Prerequisites

To get the most from this course, you should have:

  • Basic understanding of genetic concepts (IBD, SNPs, etc.)
  • Familiarity with Python programming
  • Basic knowledge of statistical concepts and probability

Research Context

The methods taught in this course stem from research exploring the intersection of biological and sociocultural anthropology through genetic genealogy, focusing on connections between Africa and its historic diaspora. We employ computational techniques to reconstruct genetic genealogy networks spanning up to nine generations, creating powerful links that connect Africans and members of the historic African diaspora in a continuum of shared family, community, and population history.

This research examines both the biological and social dimensions of genetic genealogy among persons with recent ancestors from Africa. We investigate family and ethnic identity development among African Americans using genetic genealogy to identify and interact with genetic relatives in Africa, while also studying African perspectives on these genealogical connections with descendants of ancestors displaced during the Transatlantic Slave Trade.