Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics Article Swipe
Camille Michèle Williams
,
Holly E. Poore
,
Peter T. Tanksley
,
Hyeokmoon Kweon
,
Natasia S. Courchesne‐Krak
,
Diego Londoño-Correa
,
Travis T. Mallard
,
Peter B. Barr
,
Philipp Koellinger
,
Irwin D. Waldman
,
Sandra Sanchez‐Roige
,
K. Paige Harden
,
Abraham A. Palmer
,
Danielle M. Dick
,
Richard Karlsson Linnér
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.03.21.533641
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.03.21.533641
Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci, while the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses are robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers’ use of the summary statistics.
Related Topics
Concepts
Genome-wide association study
Univariate
Multivariate statistics
Statistics
Statistical power
Summary statistics
Computer science
Biology
Mathematics
Genetics
Single-nucleotide polymorphism
Gene
Genotype
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.03.21.533641
- https://www.biorxiv.org/content/biorxiv/early/2023/03/24/2023.03.21.533641.full.pdf
- OA Status
- green
- Cited By
- 3
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4360827638
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4360827638Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.03.21.533641Digital Object Identifier
- Title
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Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary StatisticsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-03-24Full publication date if available
- Authors
-
Camille Michèle Williams, Holly E. Poore, Peter T. Tanksley, Hyeokmoon Kweon, Natasia S. Courchesne‐Krak, Diego Londoño-Correa, Travis T. Mallard, Peter B. Barr, Philipp Koellinger, Irwin D. Waldman, Sandra Sanchez‐Roige, K. Paige Harden, Abraham A. Palmer, Danielle M. Dick, Richard Karlsson LinnérList of authors in order
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https://doi.org/10.1101/2023.03.21.533641Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2023/03/24/2023.03.21.533641.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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-
greenOpen access status per OpenAlex
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https://www.biorxiv.org/content/biorxiv/early/2023/03/24/2023.03.21.533641.full.pdfDirect OA link when available
- Concepts
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Genome-wide association study, Univariate, Multivariate statistics, Statistics, Statistical power, Summary statistics, Computer science, Biology, Mathematics, Genetics, Single-nucleotide polymorphism, Gene, GenotypeTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2024: 1, 2023: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.studied. | 54 |
| abstract_inverted_index.valuable | 5 |
| abstract_inverted_index.versions | 36 |
| abstract_inverted_index.analyses, | 154, 197 |
| abstract_inverted_index.phenotype | 52 |
| abstract_inverted_index.polygenic | 166, 201 |
| abstract_inverted_index.recommend | 219 |
| abstract_inverted_index.resulting | 26 |
| abstract_inverted_index.importance | 208 |
| abstract_inverted_index.restricted | 39, 98 |
| abstract_inverted_index.statistics | 93, 226 |
| abstract_inverted_index.structural | 68 |
| abstract_inverted_index.systematic | 84 |
| abstract_inverted_index.univariate | 126 |
| abstract_inverted_index.Proprietary | 1 |
| abstract_inverted_index.advancement | 214 |
| abstract_inverted_index.association | 13 |
| abstract_inverted_index.complicated | 59 |
| abstract_inverted_index.genome-wide | 12, 186 |
| abstract_inverted_index.independent | 170 |
| abstract_inverted_index.researchers | 30 |
| abstract_inverted_index.significant | 187 |
| abstract_inverted_index.statistical | 9 |
| abstract_inverted_index.statistics. | 28, 241 |
| abstract_inverted_index.Illustrating | 100 |
| abstract_inverted_index.accompanying | 231 |
| abstract_inverted_index.correlations | 76, 160 |
| abstract_inverted_index.down-sampled | 35, 224 |
| abstract_inverted_index.multivariate | 62, 105, 136 |
| abstract_inverted_index.comparability | 89 |
| abstract_inverted_index.correlations, | 199 |
| abstract_inverted_index.documentation | 232 |
| abstract_inverted_index.down-sampling | 41, 116, 176 |
| abstract_inverted_index.externalizing | 109, 174 |
| abstract_inverted_index.gene-property | 153, 196 |
| abstract_inverted_index.investigators | 21, 221 |
| abstract_inverted_index.researchers’ | 236 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5021811638, https://openalex.org/A5081750325, https://openalex.org/A5013444958 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 15 |
| corresponding_institution_ids | https://openalex.org/I102322142, https://openalex.org/I121797337, https://openalex.org/I1314596251, https://openalex.org/I4210096112, https://openalex.org/I86519309 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/17 |
| sustainable_development_goals[0].score | 0.4399999976158142 |
| sustainable_development_goals[0].display_name | Partnerships for the goals |
| citation_normalized_percentile.value | 0.79479435 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |