Use of machine learning techniques for SNP based prediction of ancestry

Some have argued that the genetic differences between continentally defined groups are relatively small and unlikely to have biomedical significance. In this study, the extent of variation between continentally defined groups was evaluated. Small numbers of randomly selected single nucleotide polymorphisms from the International HapMap Project were used to train classifiers for prediction of ancestral continent of origin. Predictive accuracy was then tested on independent data sets. A high degree of genetic similarity implies that groups will be difficult to distinguish, especially when only a limited amount of genetic information is used. It is shown that the genetic differences between continentally defined groups are sufficiently large that one can accurately predict ancestral continent of origin using only a minute, randomly selected fraction of the genetic variation present in the human genome. Genotype data from only 50 random single nucleotide polymorphisms can be used to predict ancestral continent of origin in the primary test data set with an average accuracy of 95%.

Department dc:contributor.department

Harvard University--MIT Division of Health Sciences and Technology.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Allocco, Dominic

Advisor dc:contributor.advisor

• Isaac Kohane.

• Harvard University--MIT Division of Health Sciences and Technology.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/35550

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/35550