Literature DB >> 25388149

MeRP: a high-throughput pipeline for Mendelian randomization analysis.

Peter Yin1, Benjamin F Voight2.   

Abstract

We present a Mendelian randomization (MR) pipeline (MeRP) to facilitate rapid, causal inference analysis through automating key steps in developing and analyzing genetic instruments obtained from publicly available data. Our tool uses the National Human Genome Research Institute catalog of associations to generate instrumental variable trait files and provides methods for filtering of potential confounding associations as well as linkage disequilibrium. MeRP generates estimated causal effect scores via a MR-score analysis using summary data for disease endpoints typically found in the public domain. We utilize our pipeline to develop genetic instruments for seven traits and evaluate potential causal relationships with two disease endpoints, observing two putatively causal associations between blood pressure and bone-mineral density with type 2 diabetes. Our tool emphasizes the importance of careful but systematic screening of large datasets for discovery and systematic follow-up.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 25388149     DOI: 10.1093/bioinformatics/btu742

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

1.  Systolic Blood Pressure and Risk of Type 2 Diabetes: A Mendelian Randomization Study.

Authors:  Rachael C Aikens; Wei Zhao; Danish Saleheen; Muredach P Reilly; Stephen E Epstein; Emmi Tikkanen; Veikko Salomaa; Benjamin F Voight
Journal:  Diabetes       Date:  2016-10-04       Impact factor: 9.461

2.  Serum calcium and risk of migraine: a Mendelian randomization study.

Authors:  Peter Yin; Verneri Anttila; Katherine M Siewert; Aarno Palotie; George Davey Smith; Benjamin F Voight
Journal:  Hum Mol Genet       Date:  2017-02-15       Impact factor: 6.150

3.  Inferring the direction of a causal link and estimating its effect via a Bayesian Mendelian randomization approach.

Authors:  Ioan Gabriel Bucur; Tom Claassen; Tom Heskes
Journal:  Stat Methods Med Res       Date:  2019-05-30       Impact factor: 3.021

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.