ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data.
OBJECTIVES: There is increasing evidence that rare variants play a role in some complex traits, but their analysis is not straightforward. Locus-based tests become necessary due to low power in rare variant single-point association analyses. In addition, variant quality scores are available for sequ...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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2012
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| _version_ | 1797088041865576448 |
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| author | Asimit, J Day-Williams, A Morris, A Zeggini, E |
| author_facet | Asimit, J Day-Williams, A Morris, A Zeggini, E |
| author_sort | Asimit, J |
| collection | OXFORD |
| description | OBJECTIVES: There is increasing evidence that rare variants play a role in some complex traits, but their analysis is not straightforward. Locus-based tests become necessary due to low power in rare variant single-point association analyses. In addition, variant quality scores are available for sequencing data, but are rarely taken into account. Here, we propose two locus-based methods that incorporate variant quality scores: a regression-based collapsing approach and an allele-matching method. METHODS: Using simulated sequencing data we compare 4 locus-based tests of trait association under different scenarios of data quality. We test two collapsing-based approaches and two allele-matching-based approaches, taking into account variant quality scores and ignoring variant quality scores. We implement the collapsing and allele-matching approaches accounting for variant quality in the freely available ARIEL and AMELIA software. RESULTS: The incorporation of variant quality scores in locus-based association tests has power advantages over weighting each variant equally. The allele-matching methods are robust to the presence of both protective and risk variants in a locus, while collapsing methods exhibit a dramatic loss of power in this scenario. CONCLUSIONS: The incorporation of variant quality scores should be a standard protocol when performing locus-based association analysis on sequencing data. The ARIEL and AMELIA software implement collapsing and allele-matching locus association analysis methods, respectively, that allow the incorporation of variant quality scores. |
| first_indexed | 2024-03-07T02:44:14Z |
| format | Journal article |
| id | oxford-uuid:ab7f53d9-b648-440e-99e7-0fd11974b565 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T02:44:14Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | oxford-uuid:ab7f53d9-b648-440e-99e7-0fd11974b5652022-03-27T03:22:17ZARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ab7f53d9-b648-440e-99e7-0fd11974b565EnglishSymplectic Elements at Oxford2012Asimit, JDay-Williams, AMorris, AZeggini, EOBJECTIVES: There is increasing evidence that rare variants play a role in some complex traits, but their analysis is not straightforward. Locus-based tests become necessary due to low power in rare variant single-point association analyses. In addition, variant quality scores are available for sequencing data, but are rarely taken into account. Here, we propose two locus-based methods that incorporate variant quality scores: a regression-based collapsing approach and an allele-matching method. METHODS: Using simulated sequencing data we compare 4 locus-based tests of trait association under different scenarios of data quality. We test two collapsing-based approaches and two allele-matching-based approaches, taking into account variant quality scores and ignoring variant quality scores. We implement the collapsing and allele-matching approaches accounting for variant quality in the freely available ARIEL and AMELIA software. RESULTS: The incorporation of variant quality scores in locus-based association tests has power advantages over weighting each variant equally. The allele-matching methods are robust to the presence of both protective and risk variants in a locus, while collapsing methods exhibit a dramatic loss of power in this scenario. CONCLUSIONS: The incorporation of variant quality scores should be a standard protocol when performing locus-based association analysis on sequencing data. The ARIEL and AMELIA software implement collapsing and allele-matching locus association analysis methods, respectively, that allow the incorporation of variant quality scores. |
| spellingShingle | Asimit, J Day-Williams, A Morris, A Zeggini, E ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data. |
| title | ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data. |
| title_full | ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data. |
| title_fullStr | ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data. |
| title_full_unstemmed | ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data. |
| title_short | ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data. |
| title_sort | ariel and amelia testing for an accumulation of rare variants using next generation sequencing data |
| work_keys_str_mv | AT asimitj arielandameliatestingforanaccumulationofrarevariantsusingnextgenerationsequencingdata AT daywilliamsa arielandameliatestingforanaccumulationofrarevariantsusingnextgenerationsequencingdata AT morrisa arielandameliatestingforanaccumulationofrarevariantsusingnextgenerationsequencingdata AT zegginie arielandameliatestingforanaccumulationofrarevariantsusingnextgenerationsequencingdata |