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ugli [2025/05/15 10:53] – sylviaugli [2025/08/13 13:56] (current) – petra_vinke
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 Genome-wide association (GWAS) data is highly valuable for biobanks such as Lifelines in identifying disease/trait associations, predicting future disease development and personalized treatment.\\ Genome-wide association (GWAS) data is highly valuable for biobanks such as Lifelines in identifying disease/trait associations, predicting future disease development and personalized treatment.\\
 To facilitate the generation, analysis and study of genetic data in Lifelines, the UGLI consortium was founded. UGLI brings together many groups and PIs within the UMCG, RUG and beyond that are interested in performing such research with Lifelines data. They have brought the funding together which led to the initial genotyping of a total of 38,030 + 29,366 Lifelines participants, including [[children]], as part of the [[http://glimdna.org|HUGE]] consortium in Rotterdam on the Infinium Global Screening Array® (GSA) MultiEthnic Disease Version 1.0 and the FinnGen Thermo Fisher Axiom® custom array (resp.). Together with 15,400 samples already genotyped on the CytoSNP array ([[GWAS]]), three quality controlled GWAS datasets with a combined sample size of n~80,000 subjects are available. Genotyping of the remaining Lifelines participants is still ongoing.\\ To facilitate the generation, analysis and study of genetic data in Lifelines, the UGLI consortium was founded. UGLI brings together many groups and PIs within the UMCG, RUG and beyond that are interested in performing such research with Lifelines data. They have brought the funding together which led to the initial genotyping of a total of 38,030 + 29,366 Lifelines participants, including [[children]], as part of the [[http://glimdna.org|HUGE]] consortium in Rotterdam on the Infinium Global Screening Array® (GSA) MultiEthnic Disease Version 1.0 and the FinnGen Thermo Fisher Axiom® custom array (resp.). Together with 15,400 samples already genotyped on the CytoSNP array ([[GWAS]]), three quality controlled GWAS datasets with a combined sample size of n~80,000 subjects are available. Genotyping of the remaining Lifelines participants is still ongoing.\\
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 ===== UGLI1 - GSA ===== ===== UGLI1 - GSA =====
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 Raw intensity data from the GSA will be made available to the researchers.  Raw intensity data from the GSA will be made available to the researchers. 
  
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 ===== UGLI2 - Affymetrix ===== ===== UGLI2 - Affymetrix =====
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 ====SNP array intensity files==== ====SNP array intensity files====
 Raw intensity data from the FinnGen Thermo Fisher Axiom® custom array will be made available to the researchers.  Raw intensity data from the FinnGen Thermo Fisher Axiom® custom array will be made available to the researchers. 
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 ===== UGLI3 ===== ===== UGLI3 =====
 TBA TBA
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 ===== Overlap between studies===== ===== Overlap between studies=====
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 | GWAS4       | 938        | | GWAS4       | 938        |
 Table 2: A number of participants in UGLI1 also participated in other studies, i.e. [[deep|DAG1]], [[dag3|DAG3]], [[dag2|DAG2]]/[[http://www.nlgenome.nl/|GoNL]] and [[gwas|GWAS4]]. In the second column the sample sizes that overlap between these studies and UGLI1 can be found. For DAG1 and DAG3 these are approximations.   Table 2: A number of participants in UGLI1 also participated in other studies, i.e. [[deep|DAG1]], [[dag3|DAG3]], [[dag2|DAG2]]/[[http://www.nlgenome.nl/|GoNL]] and [[gwas|GWAS4]]. In the second column the sample sizes that overlap between these studies and UGLI1 can be found. For DAG1 and DAG3 these are approximations.  
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 =====UGLI-data release===== =====UGLI-data release=====
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 | PLINK    | PLINK is a command line program written in C/C++  | | PLINK    | PLINK is a command line program written in C/C++  |
  
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 +===== Publications with UGLI data =====
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 +  * Li et al. 2024 [[https://academic.oup.com/gpb/article/22/2/qzae031/7649324?login=false|Genome-wide Studies Reveal Genetic Risk Factors for Hepatic Fat Content]], Genomics, Proteomics & Bioinformatics, 22(2):qzae031
 +  * Keaton et al. 2024 [[https://www.nature.com/articles/s41588-024-01714-w | Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits]] Nature Genetics. 56(5):778-791
 +  * Qiao et al. 2023 [[https://www.nature.com/articles/s41467-023-36013-1 | Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose]] Nature Communications. 14(1):451
 +  * Warmerdam et al. 2022 [[https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1010135 | Increased genetic contribution to wellbeing during the COVID-19 pandemic]] PLoS Genetics. 18(5):e1010135
 +  * Nolte et al. 2017 [[https://www.nature.com/articles/ejhg201750 | Missing heritability: is the gap closing? An analysis of 32 complex traits in the Lifelines Cohort Study]] Eur J Hum Genet. 25(7):877-885
  
  
ugli.1747306408.txt.gz · Last modified: by sylvia