MaGIC: a program to generate targeted marker sets for genome-wide association studies
High-throughput genotyping technologies such as DNA pooling and DNA microarrays mean that whole-genome screens are now practical for complex disease gene discovery using association studies. Because it is currently impractical to use all available markers, a subset is typically selected on the basis...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2004-12-01
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| Series: | BioTechniques |
| Online Access: | https://www.future-science.com/doi/10.2144/04376BIN03 |
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| author | Claire L. Simpson Valerie K. Hansen Pak C. Sham Andrew Collins John F. Powell Ammar Al-Chalabi |
| author_facet | Claire L. Simpson Valerie K. Hansen Pak C. Sham Andrew Collins John F. Powell Ammar Al-Chalabi |
| author_sort | Claire L. Simpson |
| collection | DOAJ |
| description | High-throughput genotyping technologies such as DNA pooling and DNA microarrays mean that whole-genome screens are now practical for complex disease gene discovery using association studies. Because it is currently impractical to use all available markers, a subset is typically selected on the basis of required saturation density. Restricting markers to those within annotated genomic features of interest (e.g., genes or exons) or within feature-rich regions, reduces workload and cost while retaining much information. We have designed a program (MaGIC) that exploits genome assembly data to create lists of markers correlated with other genomic features. Marker lists are generated at a user-defined spacing and can target features with a user-defined density. Maps are in base pairs or linkage disequilibrium units (LDUs) as derived from the International HapMap data, which is useful for association studies and fine-mapping. Markers may be selected on the basis of heterozygosity and source database, and single nucleotide polymorphism (SNP) markers may additionally be selected on the basis of validation status. The import function means the method can be used for any genomic features such as housekeeping genes, long interspersed elements (LINES), or Alu repeats in humans, and is also functional for other species with equivalent data. The program and source code is freely available at http://cogent.iop.kcl.ac.uk/MaGIC.cogx. |
| format | Article |
| id | doaj-art-38dbb46dfbca4abe8d4b7a9cb6ae8e87 |
| institution | OA Journals |
| issn | 0736-6205 1940-9818 |
| language | English |
| publishDate | 2004-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | BioTechniques |
| spelling | doaj-art-38dbb46dfbca4abe8d4b7a9cb6ae8e872025-08-20T02:26:07ZengTaylor & Francis GroupBioTechniques0736-62051940-98182004-12-0137699699910.2144/04376BIN03MaGIC: a program to generate targeted marker sets for genome-wide association studiesClaire L. Simpson0Valerie K. Hansen1Pak C. Sham2Andrew Collins3John F. Powell4Ammar Al-Chalabi51Institute of Psychiatry, Kings College London, London, UK1Institute of Psychiatry, Kings College London, London, UK1Institute of Psychiatry, Kings College London, London, UK3University of Southampton, Southampton, UK1Institute of Psychiatry, Kings College London, London, UK1Institute of Psychiatry, Kings College London, London, UKHigh-throughput genotyping technologies such as DNA pooling and DNA microarrays mean that whole-genome screens are now practical for complex disease gene discovery using association studies. Because it is currently impractical to use all available markers, a subset is typically selected on the basis of required saturation density. Restricting markers to those within annotated genomic features of interest (e.g., genes or exons) or within feature-rich regions, reduces workload and cost while retaining much information. We have designed a program (MaGIC) that exploits genome assembly data to create lists of markers correlated with other genomic features. Marker lists are generated at a user-defined spacing and can target features with a user-defined density. Maps are in base pairs or linkage disequilibrium units (LDUs) as derived from the International HapMap data, which is useful for association studies and fine-mapping. Markers may be selected on the basis of heterozygosity and source database, and single nucleotide polymorphism (SNP) markers may additionally be selected on the basis of validation status. The import function means the method can be used for any genomic features such as housekeeping genes, long interspersed elements (LINES), or Alu repeats in humans, and is also functional for other species with equivalent data. The program and source code is freely available at http://cogent.iop.kcl.ac.uk/MaGIC.cogx.https://www.future-science.com/doi/10.2144/04376BIN03 |
| spellingShingle | Claire L. Simpson Valerie K. Hansen Pak C. Sham Andrew Collins John F. Powell Ammar Al-Chalabi MaGIC: a program to generate targeted marker sets for genome-wide association studies BioTechniques |
| title | MaGIC: a program to generate targeted marker sets for genome-wide association studies |
| title_full | MaGIC: a program to generate targeted marker sets for genome-wide association studies |
| title_fullStr | MaGIC: a program to generate targeted marker sets for genome-wide association studies |
| title_full_unstemmed | MaGIC: a program to generate targeted marker sets for genome-wide association studies |
| title_short | MaGIC: a program to generate targeted marker sets for genome-wide association studies |
| title_sort | magic a program to generate targeted marker sets for genome wide association studies |
| url | https://www.future-science.com/doi/10.2144/04376BIN03 |
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