Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees
<p dir="ltr">Genotype imputation is widely used in genome-wide association studies to boost variant density, allowing increased power in association testing. Many studies currently include pedigree data due to increasing interest in rare variants coupled with the availability of appr...
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2018
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| _version_ | 1864513520778870784 |
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| author | Ehsan Ullah (2698921) |
| author2 | Raghvendra Mall (581171) Mostafa M. Abbas (17058093) Khalid Kunji (828224) Alejandro Q. Nato (18619228) Halima Bensmail (10400) Ellen M. Wijsman (18619231) Mohamad Saad (214545) |
| author2_role | author author author author author author author |
| author_facet | Ehsan Ullah (2698921) Raghvendra Mall (581171) Mostafa M. Abbas (17058093) Khalid Kunji (828224) Alejandro Q. Nato (18619228) Halima Bensmail (10400) Ellen M. Wijsman (18619231) Mohamad Saad (214545) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ehsan Ullah (2698921) Raghvendra Mall (581171) Mostafa M. Abbas (17058093) Khalid Kunji (828224) Alejandro Q. Nato (18619228) Halima Bensmail (10400) Ellen M. Wijsman (18619231) Mohamad Saad (214545) |
| dc.date.none.fl_str_mv | 2018-12-04T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1101/gr.236315.118 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Comparison_and_assessment_of_family-_and_population-based_genotype_imputation_methods_in_large_pedigrees/25908358 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biological sciences Genetics Variant density Association testing Pedigree data Rare variants Population-based imputation Family-based imputation Ped_Pop method |
| dc.title.none.fl_str_mv | Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Genotype imputation is widely used in genome-wide association studies to boost variant density, allowing increased power in association testing. Many studies currently include pedigree data due to increasing interest in rare variants coupled with the availability of appropriate analysis tools. The performance of population-based (subjects are unrelated) imputation methods is well established. However, the performance of family- and population-based imputation methods on family data has been subject to much less scrutiny. Here, we extensively compare several family- and population-based imputation methods on family data of large pedigrees with both European and African ancestry. Our comparison includes many widely used family- and population-based tools and another method, Ped_Pop, which combines family- and population-based imputation results. We also compare four subject selection strategies for full sequencing to serve as the reference panel for imputation: GIGI-Pick, ExomePicks, PRIMUS, and random selection. Moreover, we compare two imputation accuracy metrics: the Imputation Quality Score and Pearson's correlation R<sup>2</sup> for predicting power of association analysis using imputation results. Our results show that (1) GIGI outperforms Merlin; (2) family-based imputation outperforms population-based imputation for rare variants but not for common ones; (3) combining family- and population-based imputation outperforms all imputation approaches for all minor allele frequencies; (4) GIGI-Pick gives the best selection strategy based on the R<sup>2</sup> criterion; and (5) R<sup>2</sup> is the best measure of imputation accuracy. Our study is the first to extensively evaluate the imputation performance of many available family- and population-based tools on the same family data and provides guidelines for future studies.</p><p><br></p><h2>Other Information</h2><p dir="ltr">Published in: Genome Research<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1101/gr.236315.118" target="_blank">https://dx.doi.org/10.1101/gr.236315.118</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_f7693b94d6da8be2cf4494567748f25c |
| identifier_str_mv | 10.1101/gr.236315.118 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25908358 |
| publishDate | 2018 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Comparison and assessment of family- and population-based genotype imputation methods in large pedigreesEhsan Ullah (2698921)Raghvendra Mall (581171)Mostafa M. Abbas (17058093)Khalid Kunji (828224)Alejandro Q. Nato (18619228)Halima Bensmail (10400)Ellen M. Wijsman (18619231)Mohamad Saad (214545)Biological sciencesGeneticsVariant densityAssociation testingPedigree dataRare variantsPopulation-based imputationFamily-based imputationPed_Pop method<p dir="ltr">Genotype imputation is widely used in genome-wide association studies to boost variant density, allowing increased power in association testing. Many studies currently include pedigree data due to increasing interest in rare variants coupled with the availability of appropriate analysis tools. The performance of population-based (subjects are unrelated) imputation methods is well established. However, the performance of family- and population-based imputation methods on family data has been subject to much less scrutiny. Here, we extensively compare several family- and population-based imputation methods on family data of large pedigrees with both European and African ancestry. Our comparison includes many widely used family- and population-based tools and another method, Ped_Pop, which combines family- and population-based imputation results. We also compare four subject selection strategies for full sequencing to serve as the reference panel for imputation: GIGI-Pick, ExomePicks, PRIMUS, and random selection. Moreover, we compare two imputation accuracy metrics: the Imputation Quality Score and Pearson's correlation R<sup>2</sup> for predicting power of association analysis using imputation results. Our results show that (1) GIGI outperforms Merlin; (2) family-based imputation outperforms population-based imputation for rare variants but not for common ones; (3) combining family- and population-based imputation outperforms all imputation approaches for all minor allele frequencies; (4) GIGI-Pick gives the best selection strategy based on the R<sup>2</sup> criterion; and (5) R<sup>2</sup> is the best measure of imputation accuracy. Our study is the first to extensively evaluate the imputation performance of many available family- and population-based tools on the same family data and provides guidelines for future studies.</p><p><br></p><h2>Other Information</h2><p dir="ltr">Published in: Genome Research<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1101/gr.236315.118" target="_blank">https://dx.doi.org/10.1101/gr.236315.118</a></p>2018-12-04T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1101/gr.236315.118https://figshare.com/articles/journal_contribution/Comparison_and_assessment_of_family-_and_population-based_genotype_imputation_methods_in_large_pedigrees/25908358CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/259083582018-12-04T03:00:00Z |
| spellingShingle | Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees Ehsan Ullah (2698921) Biological sciences Genetics Variant density Association testing Pedigree data Rare variants Population-based imputation Family-based imputation Ped_Pop method |
| status_str | publishedVersion |
| title | Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees |
| title_full | Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees |
| title_fullStr | Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees |
| title_full_unstemmed | Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees |
| title_short | Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees |
| title_sort | Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees |
| topic | Biological sciences Genetics Variant density Association testing Pedigree data Rare variants Population-based imputation Family-based imputation Ped_Pop method |