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Simulating genetic variant data for ...
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University of Southern California., Biostatistics.
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Simulating genetic variant data for structured populations using an approximate coalescent algorithm.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Simulating genetic variant data for structured populations using an approximate coalescent algorithm./
作者:
Jung, Hsuan.
面頁冊數:
50 p.
附註:
Adviser: Paul Marjoram.
Contained By:
Masters Abstracts International45-05.
標題:
Biology, Genetics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1443897
Simulating genetic variant data for structured populations using an approximate coalescent algorithm.
Jung, Hsuan.
Simulating genetic variant data for structured populations using an approximate coalescent algorithm.
- 50 p.
Adviser: Paul Marjoram.
Thesis (M.S.)--University of Southern California, 2007.
In this thesis we develop a program for simulating genetic variants data over long chromosomal region for structured populations. We also implement a simplified version of the algorithm for gene conversion. We show that when recombination, but not gene conversion, is present, the program generates data that is a very close approximation to that generated by the full coalescent model (in terms of LD), given that the migration rate is not too low. The implementation of gene conversion, however, does not yield the same desirable result. However, the program takes less than 2 hours to generate whole chromosomal data, which is impossible given conventional techniques.Subjects--Topical Terms:
1017730
Biology, Genetics.
Simulating genetic variant data for structured populations using an approximate coalescent algorithm.
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In this thesis we develop a program for simulating genetic variants data over long chromosomal region for structured populations. We also implement a simplified version of the algorithm for gene conversion. We show that when recombination, but not gene conversion, is present, the program generates data that is a very close approximation to that generated by the full coalescent model (in terms of LD), given that the migration rate is not too low. The implementation of gene conversion, however, does not yield the same desirable result. However, the program takes less than 2 hours to generate whole chromosomal data, which is impossible given conventional techniques.
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