Efficient haplotyping for families
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1721.1/58453 |
| _version_ | 1811092309114093568 |
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| author | Williams, Amy Lynne, Ph.D. Massachusetts Institute of Technology |
| author2 | David K. Gifford. |
| author_facet | David K. Gifford. Williams, Amy Lynne, Ph.D. Massachusetts Institute of Technology |
| author_sort | Williams, Amy Lynne, Ph.D. Massachusetts Institute of Technology |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. |
| first_indexed | 2024-09-23T15:16:22Z |
| format | Thesis |
| id | mit-1721.1/58453 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T15:16:22Z |
| publishDate | 2010 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/584532019-04-13T00:07:27Z Efficient haplotyping for families Williams, Amy Lynne, Ph.D. Massachusetts Institute of Technology David K. Gifford. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 81-83). Hapi is a novel dynamic programming algorithm for haplotyping nuclear families that outperforms contemporary family-based haplotyping algorithms. Haplotypes are useful for mapping and identifying genes which cause and contribute to the etiology of human disease, and for analyzing the products of meiosis to locate recombinations, enabling the identification of recombination hotspots and gene conversions. They can also be used to study population history, including expansion, contraction, and migration patterns in humans and other species. Hapi's efficiency is a result of eliminating or ignoring states and state transitions that are unnecessary for computing haplotypes. When applied to a dataset containing 103 families, Hapi performs over 3.8-320 times faster than state-of-the-art algorithms. These efficiency gains are practically important as they enable Hapi to haplotype family datasets which current algorithms are either unable to handle or are impractical for because of time constraints. Hapi infers both minimum-recombinant and maximum likelihood haplotypes, and because it applies to related individuals, the haplotypes it infers are highly accurate over large genomic distances. by Amy Lynne Williams. Ph.D. 2010-09-03T18:54:56Z 2010-09-03T18:54:56Z 2010 2010 Thesis http://hdl.handle.net/1721.1/58453 635472064 eng 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. http://dspace.mit.edu/handle/1721.1/7582 83 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Williams, Amy Lynne, Ph.D. Massachusetts Institute of Technology Efficient haplotyping for families |
| title | Efficient haplotyping for families |
| title_full | Efficient haplotyping for families |
| title_fullStr | Efficient haplotyping for families |
| title_full_unstemmed | Efficient haplotyping for families |
| title_short | Efficient haplotyping for families |
| title_sort | efficient haplotyping for families |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/58453 |
| work_keys_str_mv | AT williamsamylynnephdmassachusettsinstituteoftechnology efficienthaplotypingforfamilies |