Joint tests for quantitative trait loci in experimental crosses
<p>Abstract</p> <p>Selective genotyping is common because it can increase the expected correlation between QTL genotype and phenotype and thus increase the statistical power of linkage tests (<it>i.e.</it>, <it>regression-based </it>tests). Linkage can also...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | deu |
| Published: |
BMC
2004-11-01
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| Series: | Genetics Selection Evolution |
| Subjects: | |
| Online Access: | http://www.gsejournal.org/content/36/6/601 |
| _version_ | 1818963707653259264 |
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| author | Xu Shizhong Amos Christopher I Travis Elizabeth L Bullard Daniel C Yi Nengjun Yang Dongyan Beasley T Mark Allison David B |
| author_facet | Xu Shizhong Amos Christopher I Travis Elizabeth L Bullard Daniel C Yi Nengjun Yang Dongyan Beasley T Mark Allison David B |
| author_sort | Xu Shizhong |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Selective genotyping is common because it can increase the expected correlation between QTL genotype and phenotype and thus increase the statistical power of linkage tests (<it>i.e.</it>, <it>regression-based </it>tests). Linkage can also be tested by assessing whether the marginal genotypic distribution conforms to its expectation, a <it>marginal-based </it>test. We developed a class of joint tests that, by constraining intercepts in regression-based analyses, capitalize on the information available in both <it>regression-based </it>and <it>marginal-based </it>tests. We simulated data corresponding to the null hypothesis of no QTL effect and the alternative of some QTL effect at the locus for a backcross and an F2 intercross between inbred strains. Regression-based and marginal-based tests were compared to corresponding joint tests. We studied the effects of random sampling, selective sampling from a single tail of the phenotypic distribution, and selective sampling from both tails of the phenotypic distribution. Joint tests were nearly as powerful as all competing alternatives for random sampling and two-tailed selection under both backcross and F2 intercross situations. Joint tests were generally more powerful for one-tailed selection under both backcross and F2 intercross situations. However, joint tests cannot be recommended for one-tailed selective genotyping if segregation distortion is suspected.</p> |
| first_indexed | 2024-12-20T12:49:30Z |
| format | Article |
| id | doaj.art-7a0e45f571cf45819766edf61e85c878 |
| institution | Directory Open Access Journal |
| issn | 0999-193X 1297-9686 |
| language | deu |
| last_indexed | 2024-12-20T12:49:30Z |
| publishDate | 2004-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Genetics Selection Evolution |
| spelling | doaj.art-7a0e45f571cf45819766edf61e85c8782022-12-21T19:40:11ZdeuBMCGenetics Selection Evolution0999-193X1297-96862004-11-0136660161910.1186/1297-9686-36-6-601Joint tests for quantitative trait loci in experimental crossesXu ShizhongAmos Christopher ITravis Elizabeth LBullard Daniel CYi NengjunYang DongyanBeasley T MarkAllison David B<p>Abstract</p> <p>Selective genotyping is common because it can increase the expected correlation between QTL genotype and phenotype and thus increase the statistical power of linkage tests (<it>i.e.</it>, <it>regression-based </it>tests). Linkage can also be tested by assessing whether the marginal genotypic distribution conforms to its expectation, a <it>marginal-based </it>test. We developed a class of joint tests that, by constraining intercepts in regression-based analyses, capitalize on the information available in both <it>regression-based </it>and <it>marginal-based </it>tests. We simulated data corresponding to the null hypothesis of no QTL effect and the alternative of some QTL effect at the locus for a backcross and an F2 intercross between inbred strains. Regression-based and marginal-based tests were compared to corresponding joint tests. We studied the effects of random sampling, selective sampling from a single tail of the phenotypic distribution, and selective sampling from both tails of the phenotypic distribution. Joint tests were nearly as powerful as all competing alternatives for random sampling and two-tailed selection under both backcross and F2 intercross situations. Joint tests were generally more powerful for one-tailed selection under both backcross and F2 intercross situations. However, joint tests cannot be recommended for one-tailed selective genotyping if segregation distortion is suspected.</p>http://www.gsejournal.org/content/36/6/601joint testsquantitative trait locilinkageF2 crossbackcross |
| spellingShingle | Xu Shizhong Amos Christopher I Travis Elizabeth L Bullard Daniel C Yi Nengjun Yang Dongyan Beasley T Mark Allison David B Joint tests for quantitative trait loci in experimental crosses Genetics Selection Evolution joint tests quantitative trait loci linkage F2 cross backcross |
| title | Joint tests for quantitative trait loci in experimental crosses |
| title_full | Joint tests for quantitative trait loci in experimental crosses |
| title_fullStr | Joint tests for quantitative trait loci in experimental crosses |
| title_full_unstemmed | Joint tests for quantitative trait loci in experimental crosses |
| title_short | Joint tests for quantitative trait loci in experimental crosses |
| title_sort | joint tests for quantitative trait loci in experimental crosses |
| topic | joint tests quantitative trait loci linkage F2 cross backcross |
| url | http://www.gsejournal.org/content/36/6/601 |
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