Global, pathway and gene coverage of three Illumina arrays with respect to inflammatory and immune-related pathways

Tozzi, Viola; Rosenberger, Albert; Kube, Dieter; Bickeböller, Heike

doi:10.1038/s41431-019-0441-2

Cited by 5 publications

(6 citation statements)

References 18 publications

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“…Imputation is a cost-effective tool for GWAS to fill gaps of non-genotyped variants instead of whole-genome sequencing for all recruited individuals, since global coverage in genomic information of available arrays with less than 1 million SNPs not exceeds 25% [ 10 , 24 ]. However, imputation accuracy matters.…”

Section: Discussionmentioning

confidence: 99%

“…9 Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. 10 Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen, Denmark. 11 Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA.…”

Section: Abbreviationsmentioning

confidence: 99%

“…However, imputation requires advanced statistical methods for data analysis and may introduce extra uncertainty in interpreting findings. Further, only DNA variants that have previously been genotyped in the used reference panel can be imputed [ 4 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

“…CARET is funded by the National Cancer Institute, National Institutes of Health through grants U01 CA063673, UM1 CA167462, R01 CA 111703, RO1 CA 151989, U01 CA167462 and funds from the Fred Hutchinson Cancer Research Center. Other individual funding for participating studies and members of INTEGRAL-ILCCO are listed elsewhere [ 10 , 30 ]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.…”

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confidence: 99%

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

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Abbreviationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

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“…DNA was extracted from dried blood spots using Zymo Quick-DNA extraction Kits. Participants will eventually be genotyped using Illumina's Infinium Global Screening Array v1.0 (GSA) from Illumina ( 77 ), which includes 642,824 SNPs. Genotypic calls and CNV analysis will be performed using the Genome Studio 2.0 (Illumina Inc. SD, California).…”

Section: Methodsmentioning

confidence: 99%

Study Protocol: Interactive Dynamics of Coral Reef Fisheries and the Nutrition Transition in Kiribati

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Ayroles

Eurich

et al. 2022

Front. Public Health

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The Kiribati 2019 Integrated Household Income and Expenditure Survey (Integrated HIES) embeds novel ecological and human health research into an ongoing social and economic survey infrastructure implemented by the Pacific Community in partnership with national governments. This study seeks to describe the health status of a large, nationally representative sample of a geographically and socially diverse I-Kiribati population through multiple clinical measurements and detailed socio-economic surveys, while also conducting supporting food systems research on ecological, social, and institutional drivers of change. The specific hypotheses within this research relate to access to seafood and the potential nutritional and health benefits of these foods. We conducted this research in 21 of the 23 inhabited islands of Kiribati, excluding the two inhabited islands—Kanton Islands in the Phoenix Islands group with a population of 41 persons (2020 census) and Banaba Island in the Gilbert Islands group with a population of 333 persons (2020 census)—and focusing exclusively on the remaining islands in the Gilbert and Line Islands groups. Within this sample, we focused our intensive human health and ecological research in 10 of the 21 selected islands to examine the relationship between ecological conditions, resource governance, food system dynamics, and dietary patterns. Ultimately, this research has created a baseline for future Integrated HIES assessments to simultaneously monitor change in ecological, social, economic, and human health conditions and how they co-vary over time.

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