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Inferring parental genomic ancestries using pooled semi-Markov processes.

James Y Zou¹, Eran Halperin¹, Esteban Burchard²

¹Microsoft Research, One Memorial Drive, Cambridge, MA 02142, USA, Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel, Department of Bioengineering and Therapeutic Sciences and Department of Medicine, University of California, San Francisco, CA 94158 and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.

Bioinformatics (Oxford, England)

|June 15, 2015

Summary

This study introduces a novel method to determine parental genomic ancestry using DNA. The new pooled semi-Markov process accurately infers parental genetic contributions for diverse populations.

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Area of Science:

Genomics
Population Genetics
Computational Biology

Background:

Inferring parental genomic ancestry from an individual's DNA is a significant challenge.
Understanding parental contributions is crucial for studying inheritance of traits and population dynamics.

Purpose of the Study:

To develop a method for inferring parental genomic ancestries.
To quantify the fraction of each parent's genome from specific ancestries.

Main Methods:

Modeling parental genomic ancestry inference as a pooled semi-Markov process.
Developing a general mathematical framework and efficient inference algorithms for these processes.

Main Results:

Accurate inference of semi-Markov process parameters and parental genomic ancestries in Mexican and Puerto Rican trios.
Validation of the method through simulations.

Conclusions:

The developed pooled semi-Markov process and inference algorithms provide an accurate approach to parental genomic ancestry inference.
The methodology has potential applications in genomics and machine learning.