Multi-marker-LD based genetic algorithm for tag SNP selection
Despite the advances in genotyping technologies which have led to large reduction in genotyping cost, the Tag SNP Selection problem remains an important problem for computational biologists and geneticists. Selecting the smallest subset of tag SNPs that can predict the other SNPs would considerably...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | article |
| منشور في: |
2014
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/2944 http://dx.doi.org/10.1007/s12539-012-0060-x http://link.springer.com/article/10.1007/s12539-012-0060-x |
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| _version_ | 1864513459485409281 |
|---|---|
| author | Mansour, Nashat |
| author2 | Mouawad, Amer E. |
| author2_role | author |
| author_facet | Mansour, Nashat Mouawad, Amer E. |
| author_role | author |
| dc.creator.none.fl_str_mv | Mansour, Nashat Mouawad, Amer E. |
| dc.date.none.fl_str_mv | 2014 2016-01-25T07:38:10Z 2016-01-25T07:38:10Z 2016-01-25 |
| dc.identifier.none.fl_str_mv | 1913-2751 http://hdl.handle.net/10725/2944 http://dx.doi.org/10.1007/s12539-012-0060-x Mouawad, A. E., & Mansour, N. (2014). Multi-marker-LD based genetic algorithm for tag SNP selection. Interdisciplinary Sciences: Computational Life Sciences, 6(4), 303-311. http://link.springer.com/article/10.1007/s12539-012-0060-x |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Interdisciplinary Sciences |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Multi-marker-LD based genetic algorithm for tag SNP selection |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Despite the advances in genotyping technologies which have led to large reduction in genotyping cost, the Tag SNP Selection problem remains an important problem for computational biologists and geneticists. Selecting the smallest subset of tag SNPs that can predict the other SNPs would considerably minimize the complexity of genome-wide or block-based SNP-disease association studies. These studies would lead to better diagnosis and treatment of diseases. In this work, we propose three variations of a genetic algorithm based on two-marker linkage disequilibrium, multi-marker linkage disequilibrium, and a third measure that we denote by prediction power. The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. The results indicate that the multi-marker linkage disequilibrium based genetic algorithm yields better prediction accuracy. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_84d61e21b8dad6b3abd4b1edc4ae97e8 |
| identifier_str_mv | 1913-2751 Mouawad, A. E., & Mansour, N. (2014). Multi-marker-LD based genetic algorithm for tag SNP selection. Interdisciplinary Sciences: Computational Life Sciences, 6(4), 303-311. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/2944 |
| publishDate | 2014 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Multi-marker-LD based genetic algorithm for tag SNP selectionMansour, NashatMouawad, Amer E.Despite the advances in genotyping technologies which have led to large reduction in genotyping cost, the Tag SNP Selection problem remains an important problem for computational biologists and geneticists. Selecting the smallest subset of tag SNPs that can predict the other SNPs would considerably minimize the complexity of genome-wide or block-based SNP-disease association studies. These studies would lead to better diagnosis and treatment of diseases. In this work, we propose three variations of a genetic algorithm based on two-marker linkage disequilibrium, multi-marker linkage disequilibrium, and a third measure that we denote by prediction power. The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. The results indicate that the multi-marker linkage disequilibrium based genetic algorithm yields better prediction accuracy.PublishedN/A2016-01-25T07:38:10Z2016-01-25T07:38:10Z20142016-01-25Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1913-2751http://hdl.handle.net/10725/2944http://dx.doi.org/10.1007/s12539-012-0060-xMouawad, A. E., & Mansour, N. (2014). Multi-marker-LD based genetic algorithm for tag SNP selection. Interdisciplinary Sciences: Computational Life Sciences, 6(4), 303-311.http://link.springer.com/article/10.1007/s12539-012-0060-xenInterdisciplinary Sciencesinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/29442017-04-10T10:57:55Z |
| spellingShingle | Multi-marker-LD based genetic algorithm for tag SNP selection Mansour, Nashat |
| status_str | publishedVersion |
| title | Multi-marker-LD based genetic algorithm for tag SNP selection |
| title_full | Multi-marker-LD based genetic algorithm for tag SNP selection |
| title_fullStr | Multi-marker-LD based genetic algorithm for tag SNP selection |
| title_full_unstemmed | Multi-marker-LD based genetic algorithm for tag SNP selection |
| title_short | Multi-marker-LD based genetic algorithm for tag SNP selection |
| title_sort | Multi-marker-LD based genetic algorithm for tag SNP selection |
| url | http://hdl.handle.net/10725/2944 http://dx.doi.org/10.1007/s12539-012-0060-x http://link.springer.com/article/10.1007/s12539-012-0060-x |