A new multipoint method for genome-wide association studies by imputation of genotypes.
Genome-wide association studies are set to become the method of choice for uncovering the genetic basis of human diseases. A central challenge in this area is the development of powerful multipoint methods that can detect causal variants that have not been directly genotyped. We propose a coherent a...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2007
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| _version_ | 1797081553475469312 |
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| author | Marchini, J Howie, B Myers, S McVean, G Donnelly, P |
| author_facet | Marchini, J Howie, B Myers, S McVean, G Donnelly, P |
| author_sort | Marchini, J |
| collection | OXFORD |
| description | Genome-wide association studies are set to become the method of choice for uncovering the genetic basis of human diseases. A central challenge in this area is the development of powerful multipoint methods that can detect causal variants that have not been directly genotyped. We propose a coherent analysis framework that treats the problem as one involving missing or uncertain genotypes. Central to our approach is a model-based imputation method for inferring genotypes at observed or unobserved SNPs, leading to improved power over existing methods for multipoint association mapping. Using real genome-wide association study data, we show that our approach (i) is accurate and well calibrated, (ii) provides detailed views of associated regions that facilitate follow-up studies and (iii) can be used to validate and correct data at genotyped markers. A notable future use of our method will be to boost power by combining data from genome-wide scans that use different SNP sets. |
| first_indexed | 2024-03-07T01:15:52Z |
| format | Journal article |
| id | oxford-uuid:8ea21099-f9b9-4acf-93ed-4f98659e1517 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T01:15:52Z |
| publishDate | 2007 |
| record_format | dspace |
| spelling | oxford-uuid:8ea21099-f9b9-4acf-93ed-4f98659e15172022-03-26T22:59:06ZA new multipoint method for genome-wide association studies by imputation of genotypes.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:8ea21099-f9b9-4acf-93ed-4f98659e1517EnglishSymplectic Elements at Oxford2007Marchini, JHowie, BMyers, SMcVean, GDonnelly, PGenome-wide association studies are set to become the method of choice for uncovering the genetic basis of human diseases. A central challenge in this area is the development of powerful multipoint methods that can detect causal variants that have not been directly genotyped. We propose a coherent analysis framework that treats the problem as one involving missing or uncertain genotypes. Central to our approach is a model-based imputation method for inferring genotypes at observed or unobserved SNPs, leading to improved power over existing methods for multipoint association mapping. Using real genome-wide association study data, we show that our approach (i) is accurate and well calibrated, (ii) provides detailed views of associated regions that facilitate follow-up studies and (iii) can be used to validate and correct data at genotyped markers. A notable future use of our method will be to boost power by combining data from genome-wide scans that use different SNP sets. |
| spellingShingle | Marchini, J Howie, B Myers, S McVean, G Donnelly, P A new multipoint method for genome-wide association studies by imputation of genotypes. |
| title | A new multipoint method for genome-wide association studies by imputation of genotypes. |
| title_full | A new multipoint method for genome-wide association studies by imputation of genotypes. |
| title_fullStr | A new multipoint method for genome-wide association studies by imputation of genotypes. |
| title_full_unstemmed | A new multipoint method for genome-wide association studies by imputation of genotypes. |
| title_short | A new multipoint method for genome-wide association studies by imputation of genotypes. |
| title_sort | new multipoint method for genome wide association studies by imputation of genotypes |
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