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http://bura.brunel.ac.uk/handle/2438/31629
Title: | The MR-base platform supports systematic causal inference across the human phenome |
Authors: | Hemani, G Zheng, J Elsworth, B Wade, KH Haberland, V Baird, D Laurin, C Burgess, S Bowden, J Langdon, R Tan, VY Yarmolinsky, J Shihab, HA Timpson, NJ Evans, DM Relton, C Martin, RM Davey Smith, G Gaunt, TR Haycock, PC |
Issue Date: | 30-May-2018 |
Publisher: | eLife Sciences Publications |
Citation: | Hemani, G. et al. (2018) 'The MR-base platform supports systematic causal inference across the human phenome', eLife, 7, e34408, pp. 1 - 29. doi: 10.7554/eLife.34408. |
Abstract: | Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies. |
Description: | Figures and data are available online at: https://elifesciences.org/articles/34408/figures#content . |
URI: | https://bura.brunel.ac.uk/handle/2438/31629 |
DOI: | https://doi.org/10.7554/eLife.34408 |
Other Identifiers: | ORCiD: Gibran Hemani https://orcid.org/0000-0003-0920-1055 ORCiD: Jie Zheng https://orcid.org/0000-0002-6623-6839 ORCiD: Kaitlin H. Wade https://orcid.org/0000-0003-3362-6280 ORCiD: Valeriia Haberland https://orcid.org/0000-0003-4600-6013 ORCiD: Stephen Burgess https://orcid.org/0000-0001-5365-8760 ORCiD: Vanessa Y. Tan https://orcid.org/0000-0001-7938-127X ORCiD: Caroline Relton https://orcid.org/0000-0003-2052-4840 ORCiD: Richard M. Martin https://orcid.org/0000-0002-7992-7719 ORCiD: George Davey Smith https://orcid.org/0000-0002-1407-8314 ORCiD: Tom R. Gaunt https://orcid.org/0000-0003-0924-3247 ORCiD: Philip C. Haycock https://orcid.org/0000-0001-5001-3350 Article number: e34408 |
Appears in Collections: | Dept of Computer Science Research Papers |
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FullText.pdf | Copyright © 2018 Hemani et al. This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited. | 2.2 MB | Adobe PDF | View/Open |
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