EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data

Thomas W Winkler¹, Zoltan Kutalik², Mathias Gorski¹, Claudio Lottaz¹, Florian Kronenberg¹, Iris M Heid¹

Affiliations

¹ Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria.
² Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbr

PMID: 25260699
PMCID: PMC4287944
DOI: 10.1093/bioinformatics/btu621

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data

Thomas W Winkler et al. Bioinformatics. 2015.

. 2015 Jan 15;31(2):259-61.

doi: 10.1093/bioinformatics/btu621. Epub 2014 Sep 25.

Authors

Thomas W Winkler¹, Zoltan Kutalik², Mathias Gorski¹, Claudio Lottaz¹, Florian Kronenberg¹, Iris M Heid¹

Affiliations

¹ Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria.
² Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbruck, Austria Department of Genetic Epidemiology, University of Regensburg, D-93053 Regensburg, Germany, Department of Medical Genetics, University of Lausanne, CH-1005 Lausanne, Switzerland, Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), CH-1010 Lausanne, Switzerland, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland, Department of Statistical Bioinformatics, Institute for Functional Genomics, University of Regensburg, D-93053 Regensburg, Germany and Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, A-6020 Innsbr

PMID: 25260699
PMCID: PMC4287944
DOI: 10.1093/bioinformatics/btu621

Abstract

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion.

Availability: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/.

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

**Fig. 1.**
Miami-Plot showing publically available women- and men-specific association P-values for waist–hip ratio adjusted for BMI (Randall *et al.*, 2013). Known main effect loci are highlighted in green (Lindgren *et al.*, 2009) or orange (Heid *et al.*, 2010). Based on the locus coloring, one can see two novel (women-specific) loci on chromosome 3

See this image and copyright information in PMC

References

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1. Behrens G, et al. To stratify or not to stratify: power considerations for population-based genome-wide association studies of quantitative traits. Genet. Epidemiol. 2011;35:867–879. - PubMed
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1. Cox DR, Hinkley DV. Theoretical Statistics. London, New York: Chapman and Hall, Halsted Press; 1979.

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EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data

Affiliations

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data

Authors

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Abstract

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MeSH terms

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LinkOut - more resources

Full Text Sources

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