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Iam hiQ—a novel pair of accuracy indices for imputed genotypes

BACKGROUND: Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are...

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Autores principales: Rosenberger, Albert, Tozzi, Viola, Bickeböller, Heike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785528/
https://www.ncbi.nlm.nih.gov/pubmed/35073846
http://dx.doi.org/10.1186/s12859-022-04568-3
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author Rosenberger, Albert
Tozzi, Viola
Bickeböller, Heike
author_facet Rosenberger, Albert
Tozzi, Viola
Bickeböller, Heike
author_sort Rosenberger, Albert
collection PubMed
description BACKGROUND: Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand. RESULTS: Applying both measures to a large case–control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2). CONCLUSION: We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04568-3.
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spelling pubmed-87855282022-01-24 Iam hiQ—a novel pair of accuracy indices for imputed genotypes Rosenberger, Albert Tozzi, Viola Bickeböller, Heike BMC Bioinformatics Research BACKGROUND: Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand. RESULTS: Applying both measures to a large case–control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2). CONCLUSION: We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04568-3. BioMed Central 2022-01-24 /pmc/articles/PMC8785528/ /pubmed/35073846 http://dx.doi.org/10.1186/s12859-022-04568-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Rosenberger, Albert
Tozzi, Viola
Bickeböller, Heike
Iam hiQ—a novel pair of accuracy indices for imputed genotypes
title Iam hiQ—a novel pair of accuracy indices for imputed genotypes
title_full Iam hiQ—a novel pair of accuracy indices for imputed genotypes
title_fullStr Iam hiQ—a novel pair of accuracy indices for imputed genotypes
title_full_unstemmed Iam hiQ—a novel pair of accuracy indices for imputed genotypes
title_short Iam hiQ—a novel pair of accuracy indices for imputed genotypes
title_sort iam hiq—a novel pair of accuracy indices for imputed genotypes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785528/
https://www.ncbi.nlm.nih.gov/pubmed/35073846
http://dx.doi.org/10.1186/s12859-022-04568-3
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