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    Yosuke Tanigawa
    @yk-tanigawa
    Hello
    Adam Lavertu
    @alavertu
    Hiya
    Alex Poliakov
    @apoliakov
    Hey guys
    mzekavat
    @mzekavat
    Hello World
    Manuel Rivas
    @manuelrivascruz_twitter
    Welcome! More from our end soon, but seems like a great venue to ask questions/comments/early look at data while we all move activities forward
    For those interested Hail has a gitter community as well, which may be relevant for running analysis
    https://gitter.im/hail-is/hail
    James R. Priest MD
    @JamesRPriestMD_twitter
    Yo
    Joni Coleman
    @JoniColeman
    Hallo
    Monkol Lek
    @monkollek
    Hello World2
    Mark Daly
    @dalygene_twitter
    Hi all
    Manuel Rivas
    @manuelrivascruz_twitter
    Hi @dalygene_twitter :smile:
    Sara L Pulit
    @saralpulit
    Hello all!
    James R. Priest MD
    @JamesRPriestMD_twitter
    Despite the funky SNPs in the first 500k release- I think that the b-alleles & log ratios should be ok. We're gonna get started with the CNV calling, anybody want to join us?
    Manuel Rivas
    @manuelrivascruz_twitter
    Feel free to send plots :-)
    Milton Pividori
    @miltondp
    Hello
    Johanne Marie Justes
    @jmjustesen_twitter
    Hi all
    Manuel Rivas
    @manuelrivascruz_twitter
    image.png
    @/all Thrilled to have the first release of the full UK Biobank dataset at
    Global Biobank Engine: https://biobankengine.stanford.edu/ . Feel free to explore.
    Manuel Rivas
    @manuelrivascruz_twitter
    Hi @channel - I was hoping you have had a chance to browse some phenotypes. We will be discussing some of the GWAS results generated over the next few weeks here.
    There is a bigger upload coming soon as well. @/all
    rkwalters
    @rkwalters
    @manuelrivascruz_twitter Location-based searches seem to be broken at the moment
    i.e. typing your examples of 1-169519049 or 10-114686614-114786614 in the search box instead of clicking the links return an error page
    Manuel Rivas
    @manuelrivascruz_twitter
    Perfect! Thanks for the feedback
    Will update today
    Manuel Rivas
    @manuelrivascruz_twitter
    Fixed. Feel free to interrogate
    @rkwalters
    Milton Pividori
    @miltondp
    Hi all. Today I found a note regarding the sample-qc file: http://www.ukbiobank.ac.uk/wp-content/uploads/2017/07/ukb_genetic_file_description.txt
    Milton Pividori
    @miltondp
    there seems to be another version of the samples QC file, however it wasn't updated in my EGA account
    Manuel Rivas
    @manuelrivascruz_twitter
    Thanks @miltondp . @yosuke - can we compare against the sample QC file we have been using. We will make the Github repository with QC details open next week. I believe Neale lab is doing the same.
    Manuel Rivas
    @manuelrivascruz_twitter
    @/all - we will update some variant filters as well where we compare the estimated geotyped UK Biobank frequency to estimated frequencies from ExAC. This has highlighted a set of variants worthy of filtering in your studies.
    Christopher DeBoever
    @cdeboever3
    @/all, we're happy to present some new resources for the community
    We've put together some annotations and filtering information for variants on the UK Biobank arrays: https://github.com/rivas-lab/public-resources
    We've also posted a preprint with an analysis of the effect of protein truncating variants across medical phenotypes from the UK Biobank: http://www.biorxiv.org/content/early/2017/08/23/179762
    And we've released a new Shiny app for evaluating power to detect genetic associations for protein truncating variants (PTVs) in the UK Biobank and other gnomAD populations
    Christopher DeBoever
    @cdeboever3
    The app is described in this blog post which also includes a timeline of important papers on PTVs which I'm glad to update according to feedback.
    Looking forward to interacting with everyone and I'm glad to discuss these new resources here!
    Stefan Stender
    @StefanStender_twitter
    Exciting work! Quick question: is the ANKDD1B association with low risk of hypercholesterolemia due to LD with regulatory variation at the nearby HMGCR gene (the target of statins, and a known GWAS locus for LDL-C?
    Manuel Rivas
    @manuelrivascruz_twitter
    Great great question @cdeboever - good to have a look and attribute @StefanStender_twitter
    We definitely knocked out a few red herrings - as you can see from MHC and this is a central one we may have missed
    Christopher DeBoever
    @cdeboever3
    Thanks @StefanStender_twitter I will look into that.
    Josep Maria Mercader
    @josep_mercader_twitter
    Hi!
    actually entered for a question ;) Is there any documentation about how the computational grouping of phenotypes with cancer (Category 100092) registry is computed? We are trying to find some of the cancer types and the number of cases often do not match with those shown in the engine. Also, are the related pairs excluded by prioritization of cases for each phenotype, or just based on other QC metrics. Thanks!
    Christopher DeBoever
    @cdeboever3
    Hi @josep_mercader_twitter we are working on documenting the phenotype groupings. I believe the cancer phenotype case definitions are generally a combination of the cancer registry and verbal questionnaire data. We don't choose which subjects to include by prioritizing cases, we just defined a set of unrelated white-British subjects using the QC files and used that same set for all GWAS.
    Josep Maria Mercader
    @josep_mercader_twitter
    Thanks, this is very helpful!