Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping
We previously proposed a simple regression-based method to map quantitative trait loci underlying function-valued phenotypes. In order to better handle the case of noisy phenotype measurements and accommodate the correlation structure among time points, we propose an alternative approach that mainta...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Oxford University Press
2016-01-01
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| Series: | G3: Genes, Genomes, Genetics |
| Subjects: | |
| Online Access: | http://g3journal.org/lookup/doi/10.1534/g3.115.024133 |
| _version_ | 1819259487502991360 |
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| author | Il-Youp Kwak Candace R. Moore Edgar P. Spalding Karl W. Broman |
| author_facet | Il-Youp Kwak Candace R. Moore Edgar P. Spalding Karl W. Broman |
| author_sort | Il-Youp Kwak |
| collection | DOAJ |
| description | We previously proposed a simple regression-based method to map quantitative trait loci underlying function-valued phenotypes. In order to better handle the case of noisy phenotype measurements and accommodate the correlation structure among time points, we propose an alternative approach that maintains much of the simplicity and speed of the regression-based method. We overcome noisy measurements by replacing the observed data with a smooth approximation. We then apply functional principal component analysis, replacing the smoothed phenotype data with a small number of principal components. Quantitative trait locus mapping is applied to these dimension-reduced data, either with a multi-trait method or by considering the traits individually and then taking the average or maximum LOD score across traits. We apply these approaches to root gravitropism data on Arabidopsis recombinant inbred lines and further investigate their performance in computer simulations. Our methods have been implemented in the R package, funqtl. |
| first_indexed | 2024-12-23T19:10:48Z |
| format | Article |
| id | doaj.art-ec184a387da245e5a6ac74fbc2228e9b |
| institution | Directory Open Access Journal |
| issn | 2160-1836 |
| language | English |
| last_indexed | 2024-12-23T19:10:48Z |
| publishDate | 2016-01-01 |
| publisher | Oxford University Press |
| record_format | Article |
| series | G3: Genes, Genomes, Genetics |
| spelling | doaj.art-ec184a387da245e5a6ac74fbc2228e9b2022-12-21T17:34:28ZengOxford University PressG3: Genes, Genomes, Genetics2160-18362016-01-0161798610.1534/g3.115.0241338Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait MappingIl-Youp KwakCandace R. MooreEdgar P. SpaldingKarl W. BromanWe previously proposed a simple regression-based method to map quantitative trait loci underlying function-valued phenotypes. In order to better handle the case of noisy phenotype measurements and accommodate the correlation structure among time points, we propose an alternative approach that maintains much of the simplicity and speed of the regression-based method. We overcome noisy measurements by replacing the observed data with a smooth approximation. We then apply functional principal component analysis, replacing the smoothed phenotype data with a small number of principal components. Quantitative trait locus mapping is applied to these dimension-reduced data, either with a multi-trait method or by considering the traits individually and then taking the average or maximum LOD score across traits. We apply these approaches to root gravitropism data on Arabidopsis recombinant inbred lines and further investigate their performance in computer simulations. Our methods have been implemented in the R package, funqtl.http://g3journal.org/lookup/doi/10.1534/g3.115.024133QTLfunction-valued traitsmodel selectiongrowth curvesmultivariate analysis |
| spellingShingle | Il-Youp Kwak Candace R. Moore Edgar P. Spalding Karl W. Broman Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping G3: Genes, Genomes, Genetics QTL function-valued traits model selection growth curves multivariate analysis |
| title | Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping |
| title_full | Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping |
| title_fullStr | Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping |
| title_full_unstemmed | Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping |
| title_short | Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping |
| title_sort | mapping quantitative trait loci underlying function valued traits using functional principal component analysis and multi trait mapping |
| topic | QTL function-valued traits model selection growth curves multivariate analysis |
| url | http://g3journal.org/lookup/doi/10.1534/g3.115.024133 |
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