Bounds on the minimum number of recombination events in a sample history.
Recombination is an important evolutionary factor in many organisms, including humans, and understanding its effects is an important task facing geneticists. Detecting past recombination events is thus important; this article introduces statistics that give a lower bound on the number of recombinati...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2003
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| _version_ | 1797088130280456192 |
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| author | Myers, S Griffiths, R |
| author_facet | Myers, S Griffiths, R |
| author_sort | Myers, S |
| collection | OXFORD |
| description | Recombination is an important evolutionary factor in many organisms, including humans, and understanding its effects is an important task facing geneticists. Detecting past recombination events is thus important; this article introduces statistics that give a lower bound on the number of recombination events in the history of a sample, on the basis of the patterns of variation in the sample DNA. Such lower bounds are appropriate, since many recombination events in the history are typically undetectable, so the true number of historical recombinations is unobtainable. The statistics can be calculated quickly by computer and improve upon the earlier bound of Hudson and Kaplan 1985. A method is developed to combine bounds on local regions in the data to produce more powerful improved bounds. The method is flexible to different models of recombination occurrence. The approach gives recombination event bounds between all pairs of sites, to help identify regions with more detectable recombinations, and these bounds can be viewed graphically. Under coalescent simulations, there is a substantial improvement over the earlier method (of up to a factor of 2) in the expected number of recombination events detected by one of the new minima, across a wide range of parameter values. The method is applied to data from a region within the lipoprotein lipase gene and the amount of detected recombination is substantially increased. Further, there is strong clustering of detected recombination events in an area near the center of the region. A program implementing these statistics, which was used for this article, is available from http://www.stats.ox.ac.uk/mathgen/programs.html. |
| first_indexed | 2024-03-07T02:45:32Z |
| format | Journal article |
| id | oxford-uuid:abf063fe-79d1-43ab-9b2c-48b95ce74825 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T02:45:32Z |
| publishDate | 2003 |
| record_format | dspace |
| spelling | oxford-uuid:abf063fe-79d1-43ab-9b2c-48b95ce748252022-03-27T03:25:18ZBounds on the minimum number of recombination events in a sample history.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:abf063fe-79d1-43ab-9b2c-48b95ce74825EnglishSymplectic Elements at Oxford2003Myers, SGriffiths, RRecombination is an important evolutionary factor in many organisms, including humans, and understanding its effects is an important task facing geneticists. Detecting past recombination events is thus important; this article introduces statistics that give a lower bound on the number of recombination events in the history of a sample, on the basis of the patterns of variation in the sample DNA. Such lower bounds are appropriate, since many recombination events in the history are typically undetectable, so the true number of historical recombinations is unobtainable. The statistics can be calculated quickly by computer and improve upon the earlier bound of Hudson and Kaplan 1985. A method is developed to combine bounds on local regions in the data to produce more powerful improved bounds. The method is flexible to different models of recombination occurrence. The approach gives recombination event bounds between all pairs of sites, to help identify regions with more detectable recombinations, and these bounds can be viewed graphically. Under coalescent simulations, there is a substantial improvement over the earlier method (of up to a factor of 2) in the expected number of recombination events detected by one of the new minima, across a wide range of parameter values. The method is applied to data from a region within the lipoprotein lipase gene and the amount of detected recombination is substantially increased. Further, there is strong clustering of detected recombination events in an area near the center of the region. A program implementing these statistics, which was used for this article, is available from http://www.stats.ox.ac.uk/mathgen/programs.html. |
| spellingShingle | Myers, S Griffiths, R Bounds on the minimum number of recombination events in a sample history. |
| title | Bounds on the minimum number of recombination events in a sample history. |
| title_full | Bounds on the minimum number of recombination events in a sample history. |
| title_fullStr | Bounds on the minimum number of recombination events in a sample history. |
| title_full_unstemmed | Bounds on the minimum number of recombination events in a sample history. |
| title_short | Bounds on the minimum number of recombination events in a sample history. |
| title_sort | bounds on the minimum number of recombination events in a sample history |
| work_keys_str_mv | AT myerss boundsontheminimumnumberofrecombinationeventsinasamplehistory AT griffithsr boundsontheminimumnumberofrecombinationeventsinasamplehistory |