A platform for Mendelian randomisation & PheWAS using results from GWAS. Includes API, web interface and R packages https://xitter.cf/t.co/JdnVtX9S0t

Bristol, England
Joined October 2016
New postdoc opportunity in Health Data Science at the MRC Integrative Epidemiology Unit (@mrcieu) at University of Bristol. Get in touch if interested! bristol.ac.uk/jobs/find/deta…
Join me at #ElasticCC where I'll be talking about how we use Elasticsearch for @OpenGwas. This is @Elastic’s free technical event from the community, for the community — happening from Feb 26 - 27 ela.st/community-conference
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Analytical tools - The gwasglue R package connects the local or cloud data sources, as well as cloud hosted LD reference panels, to a range of third party tools. Fine mapping, colocalisation, MR, genetic correlations, PheWAS, etc. mrcieu.github.io/gwasglue/
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Local querying - All the data can also be downloaded as GWAS VCF files. There is a need for a storage format that is unambiguous, self contained and performant for querying. We designed this for large scale analysis on compute clusters bit.ly/33VbOfL
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Cloud querying - elasticsearch to store the data, hosted in collaboration with Oracle Cloud Infrastructure. We worked hard to optimise queries, allowing rapid search by position, rsid, range, p-value. This can be done in R, python or through a RESTful API.
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QC process - we align the non-effect allele to the human genome reference sequence; and annotate the positions with dbSNP identifiers. Example QC report: gwas.mrcieu.ac.uk/datasets/u…
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Data sources - To date, the summary data have been manually harvested/pooled from various GWAS consortia and biobanks. Many thanks to these studies who have made their summary data available!
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OpenGWAS (gwas.mrcieu.ac.uk/) is a harmonised database of complete GWAS summary data (126 billion associations, almost 15000 complete datasets) with programmatic connections to a range of third party analytical tools.
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Continued data harvesting - for new GWAS results that are published, upload them to the EBI GWAS catalog and we will pull them in from there. For unpublished results, or large batches, we have pipelines to do that. Get in touch here: github.com/mrcieu/opengwas-r…
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Huge thanks to @The_MRC, @OracleCloud and @wellcometrust for funding much of this, and team (@explodecomputer @tomrgaunt @elswob @matt_s_lyon @prime2 @assetweb @JonJHallett and others) for making a hopefully useful community resource
We built the OpenGWAS resource to be a free and open platform to support work on GWAS summary data. Much of it is based on extensive feedback on @mrbase2 from both internal and external colleagues. Paper here: bit.ly/2DRbHGT, key points below:
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Our multi-omics study of COVID-19 drug targets are online now 😃 medrxiv.org/content/10.1101/…
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EpiGraphDB v0.3.0 is released today, with ~10x expansion of data to support #triangulation of #epidemiology evidence and #datamining. Check out the latest and greatest features at epigraphdb.org/!
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Guidelines on performing Mendelian randomization investigations written by an all-star line-up of MR researchers are now available on Wellcome Open Research: wellcomeopenresearch.org/art… - represents a consensus statement after 12+ months of deliberation. Comments welcome!
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Latest post in our MRC-IEU software blog, Exploring Elasticsearch architectures with Oracle Cloud - ieup4.blogs.bristol.ac.uk/20…
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Want to learn about the principles, potentials and limitations of Mendelian randomization? If so this webinar run by @CDC_Genomics at 8pm UK time (3pm East Coast US time) today might be of interest cdc.gov/genomics/events/prec…
MR-TRYX: Exploiting horizontal pleiotropy to infer novel causal pathways biorxiv.org/cgi/content/shor… #bioRxiv
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