Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls
Abstract Background Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or samp...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-04-01
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| Series: | BMC Bioinformatics |
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| Online Access: | http://link.springer.com/article/10.1186/s12859-019-2727-3 |
| _version_ | 1818305664463667200 |
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| author | Miriam Gjerdevik Astanand Jugessur Øystein A. Haaland Julia Romanowska Rolv T. Lie Heather J. Cordell Håkon K. Gjessing |
| author_facet | Miriam Gjerdevik Astanand Jugessur Øystein A. Haaland Julia Romanowska Rolv T. Lie Heather J. Cordell Håkon K. Gjessing |
| author_sort | Miriam Gjerdevik |
| collection | DOAJ |
| description | Abstract Background Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or sample size is an important first step in the planning of any scientific study, there is currently a lack of software for genetic power calculations in family-based study designs. Here, we address this shortcoming through new implementations of power calculations in the R package Haplin, which is a flexible and robust software for genetic epidemiological analyses. Power calculations in Haplin can be performed analytically using the asymptotic variance-covariance structure of the parameter estimator, or else by a straightforward simulation approach. Haplin performs power calculations for child, parent-of-origin and maternal effects, as well as for gene-environment interactions. The power can be calculated for both single SNPs and haplotypes, either autosomal or X-linked. Moreover, Haplin enables power calculations for different child-parent configurations, including (but not limited to) case-parent triads, case-mother dyads, and case-parent triads in combination with unrelated control-parent triads. Results We compared the asymptotic power approximations to the power of analysis attained with Haplin. For external validation, the results were further compared to the power of analysis attained by the EMIM software using data simulations from Haplin. Consistency observed between Haplin and EMIM across various genetic scenarios confirms the computational accuracy of the inference methods used in both programs. The results also demonstrate that power calculations in Haplin are applicable to genetic association studies using either log-linear or multinomial modeling approaches. Conclusions Haplin provides a robust and reliable framework for power calculations in genetic association analyses for a wide range of genetic effects and etiologic scenarios, based on genotype data from a variety of child-parent configurations. |
| first_indexed | 2024-12-13T06:30:11Z |
| format | Article |
| id | doaj.art-0268f3bc02614412970832065092c6d7 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-13T06:30:11Z |
| publishDate | 2019-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-0268f3bc02614412970832065092c6d72022-12-21T23:56:38ZengBMCBMC Bioinformatics1471-21052019-04-0120111110.1186/s12859-019-2727-3Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controlsMiriam Gjerdevik0Astanand Jugessur1Øystein A. Haaland2Julia Romanowska3Rolv T. Lie4Heather J. Cordell5Håkon K. Gjessing6Department of Global Public Health and Primary Care, University of BergenDepartment of Global Public Health and Primary Care, University of BergenDepartment of Global Public Health and Primary Care, University of BergenDepartment of Global Public Health and Primary Care, University of BergenDepartment of Global Public Health and Primary Care, University of BergenInstitute of Genetic Medicine, Newcastle University, International Centre for LifeDepartment of Global Public Health and Primary Care, University of BergenAbstract Background Log-linear and multinomial modeling offer a flexible framework for genetic association analyses of offspring (child), parent-of-origin and maternal effects, based on genotype data from a variety of child-parent configurations. Although the calculation of statistical power or sample size is an important first step in the planning of any scientific study, there is currently a lack of software for genetic power calculations in family-based study designs. Here, we address this shortcoming through new implementations of power calculations in the R package Haplin, which is a flexible and robust software for genetic epidemiological analyses. Power calculations in Haplin can be performed analytically using the asymptotic variance-covariance structure of the parameter estimator, or else by a straightforward simulation approach. Haplin performs power calculations for child, parent-of-origin and maternal effects, as well as for gene-environment interactions. The power can be calculated for both single SNPs and haplotypes, either autosomal or X-linked. Moreover, Haplin enables power calculations for different child-parent configurations, including (but not limited to) case-parent triads, case-mother dyads, and case-parent triads in combination with unrelated control-parent triads. Results We compared the asymptotic power approximations to the power of analysis attained with Haplin. For external validation, the results were further compared to the power of analysis attained by the EMIM software using data simulations from Haplin. Consistency observed between Haplin and EMIM across various genetic scenarios confirms the computational accuracy of the inference methods used in both programs. The results also demonstrate that power calculations in Haplin are applicable to genetic association studies using either log-linear or multinomial modeling approaches. Conclusions Haplin provides a robust and reliable framework for power calculations in genetic association analyses for a wide range of genetic effects and etiologic scenarios, based on genotype data from a variety of child-parent configurations.http://link.springer.com/article/10.1186/s12859-019-2727-3Log-linear and multinomial modelsGenome-wide association studies (GWAS)Statistical power estimationSample size estimationHaplinEMIM |
| spellingShingle | Miriam Gjerdevik Astanand Jugessur Øystein A. Haaland Julia Romanowska Rolv T. Lie Heather J. Cordell Håkon K. Gjessing Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls BMC Bioinformatics Log-linear and multinomial models Genome-wide association studies (GWAS) Statistical power estimation Sample size estimation Haplin EMIM |
| title | Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls |
| title_full | Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls |
| title_fullStr | Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls |
| title_full_unstemmed | Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls |
| title_short | Haplin power analysis: a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls |
| title_sort | haplin power analysis a software module for power and sample size calculations in genetic association analyses of family triads and unrelated controls |
| topic | Log-linear and multinomial models Genome-wide association studies (GWAS) Statistical power estimation Sample size estimation Haplin EMIM |
| url | http://link.springer.com/article/10.1186/s12859-019-2727-3 |
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