{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Richardson TG"],"funding":["Medical Research Council","National Institute for Health Research (NIHR)"],"pagination":["a039248"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8168525"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["11(6)"],"pubmed_abstract":["The advent of large-scale, phenotypically rich, and readily accessible data provides an unprecedented opportunity for epidemiologists, statistical geneticists, bioinformaticians, and also behavioral and social scientists to investigate the causes and consequences of disease. Computational tools and resources are an integral component of such endeavors, which will become increasingly important as these data continue to grow exponentially. In this review, we have provided an overview of computational software and databases that have been developed to assist with analyses in causal inference. This includes online tools that can be used to help generate hypotheses, publicly accessible resources that store summary-level information for millions of genetic markers, and computational approaches t"],"journal":["Cold Spring Harbor perspectives in medicine"],"pubmed_title":["Computational Tools for Causal Inference in Genetics."],"pmcid":["PMC8168525"],"funding_grant_id":["MC_UU_00011/4"],"pubmed_authors":["Zheng J","Richardson TG","Gaunt TR"],"additional_accession":[]},"is_claimable":false,"name":"Computational Tools for Causal Inference in Genetics.","description":"The advent of large-scale, phenotypically rich, and readily accessible data provides an unprecedented opportunity for epidemiologists, statistical geneticists, bioinformaticians, and also behavioral and social scientists to investigate the causes and consequences of disease. Computational tools and resources are an integral component of such endeavors, which will become increasingly important as these data continue to grow exponentially. In this review, we have provided an overview of computational software and databases that have been developed to assist with analyses in causal inference. This includes online tools that can be used to help generate hypotheses, publicly accessible resources that store summary-level information for millions of genetic markers, and computational approaches t","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Jun","modification":"2025-04-19T10:24:07.602Z","creation":"2025-02-19T02:37:56.426Z"},"accession":"S-EPMC8168525","cross_references":{"pubmed":["33288654"],"doi":["10.1101/cshperspect.a039248"]}}