I can drive in Iceland: Enabling international joint analyses

Lunt, Chris; Denny, Joshua C.

doi:10.1016/j.xgen.2021.100034

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…For example, data that reside in an enclave may not be allowed to leave the environment in non-aggregated form 10 , 11 . Researchers wishing to safely and appropriately analyze data across different TREs face technological hurdles and policy requirements to do so 12 . Several approaches to data analysis across enclaves have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis

Deflaux,

Selvaraj,

Condon

et al. 2023

Nat Commun

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Recently, large scale genomic projects such as All of Us and the UK Biobank have introduced a new research paradigm where data are stored centrally in cloud-based Trusted Research Environments (TREs). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conduct a Genome-Wide Association Study of standard lipid measures using two approaches: meta-analysis and pooled analysis. Comparison of full summary data from both approaches with an external study shows strong correlation of known loci with lipid levels (R2 ~ 83–97%). Importantly, 90 variants meet the significance threshold only in the meta-analysis and 64 variants are significant only in pooled analysis, with approximately 20% of variants in each of those groups being most prevalent in non-European, non-Asian ancestry individuals. These findings have important implications, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.

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Section: Introductionmentioning

confidence: 99%

Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis

Deflaux,

Selvaraj,

Condon

et al. 2023

Nat Commun

Self Cite

View full text Add to dashboard Cite

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Cloud gazing: demonstrating paths for unlocking the value of cloud genomics through cross-cohort analysis

Deflaux

Selvaraj

Condon

et al. 2022

Preprint

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The rapid growth of genomic data has led to a new research paradigm where data are stored centrally in Trusted Research Environments (TREs) such as the All of Us Researcher Workbench (RW) and the UK Biobank Research Analysis Platform (RAP). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conducted a Genome-Wide Association Study (GWAS) of standard lipid measures on the UKB RAP and AoU RW using two approaches: meta-analysis and pooled analysis. We curated lipid measurements for 37,754 All of Us participants with whole genome sequence (WGS) data and 190,982 UK Biobank participants with whole exome sequence (WES) data. For the meta-analysis, we performed a GWAS of each cohort in their respective platform and meta-analyzed the results. We separately performed a pooled GWAS on both datasets combined. We identified 454 and 445 significant variants in meta-analysis and pooled analysis, respectively. Comparison of full summary data from both meta-analysis and pooled analysis with an external study showed strong correlation of known loci with lipid levels (R2~91-98%). Importantly, 84 variants met the significance threshold only in the meta-analysis and 75 variants were significant only in pooled analysis. These method-specific differences may be explained by differences in cohort size, ancestry, and phenotype distributions in All of Us and UK Biobank. Importantly, we noted a significant increase in the proportion of significant variants predominantly from non-European ancestry individuals in the pooled analysis compared to meta-analysis (p=0.01). Pooled analysis required about half as many computational steps as meta-analysis. These findings have important implications for both platform implementations and researchers undertaking large-scale cross-cohort analyses, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.

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I can drive in Iceland: Enabling international joint analyses

Cited by 2 publications

References 11 publications

Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis

Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis

Cloud gazing: demonstrating paths for unlocking the value of cloud genomics through cross-cohort analysis

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