Johanna Schachtl-Riess Profile
Johanna Schachtl-Riess

@johsr2

Followers
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Following
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Postdoc @KronenbergLab (Genetic Epidemiology) | she/her

Joined July 2019
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@lukfor
Lukas Forer
2 years
(1/3)🧬💻 Join the Genome Informatics team at the Institute of Genetic Epidemiology, Medical University of Innsbruck @imed_tweets🎓 I am seeking a PhD Student to work together on polygenic risk scores and genetic data analysis 🚀 https://t.co/fzsx8Q9TYq
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genepi.i-med.ac.at
Polygenic risk scores (PRS) represent a novel approach in the field of genetics, to improve understanding of complex traits and diseases influenced by multiple genetic factors. Unlike single-gene...
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@lukfor
Lukas Forer
2 years
nf-gwas is out in NAR Genomics and Bioinformatics 🎉! Performing highly parallelized and reproducible #GWAS analysis 🧬🔍📊 Looking forward to pushing the #Nextflow pipeline together with @seppinho, @johsr2 and @SilviaDiMaio4 to the next level 🚀 https://t.co/pBEpthhmgP
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academic.oup.com
Abstract. Genome-wide association studies (GWAS) are transforming genetic research and enable the detection of novel genotype-phenotype relationships. In t
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@KronenbergLab
The Kronenberg Lab
2 years
Happy to share our newest GWAS on PCSK9 which has been published open access in Atherosclerosis. We identified 5 novel loci for PCSK9 concentrations. See more: https://t.co/H5vwF2g3hr #PCSK9 #Atherosclerosis @society_eas @azinkh96 @ATHjournal @imed_tweets
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@seppinho
Sebastian Schönherr
2 years
.@nextflowio summit run successfully ✅ the nf-test and nf-gwas team says 🙏 for the warm welcome!! @lukfor @johsr2 @SilviaDiMaio4
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@HPC_Cloud_Rob
Rob Lalonde
2 years
@SeqeraLabs latest “Pipeline In The Spotlight'' is https://t.co/JVFnkKkv9C, a @nextflowio pipeline to perform biobank-scale genome-wide association studies on HPC or Cloud. Analyze thousands of phenotypes in parallel and explore your final results interactively in a web browser.
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@seppinho
Sebastian Schönherr
3 years
Our GWAS Nextflow pipeline now supports gene-based testing functionality (provided by regenie) and runs on all major cloud providers! Code + Docs: https://t.co/nugjQOv0L8 1/2 (pls see next tweet for credits!)
genepi.github.io
nf-gwas: A nextflow pipeline to perform genome-wide association studies (GWAS) using regenie.
@seppinho
Sebastian Schönherr
4 years
⭐⭐ Pipeline release ⭐⭐ nf-gwas: A Nextflow pipeline to run genome wide association studies (GWAS). #gwas #Bioinformatics #nextflow 👇👇
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@johsr2
Johanna Schachtl-Riess
4 years
Excited for the remaining two days #EASCongress2022 #togetheratEAS2022
@EASCongress
EAS Congress
4 years
We are in the yellow room for the first Late Breaker session. Join us #EASCongress2022
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@azinkh96
azin kheirkhah
4 years
We are clearly enjoying our time at the EAS 😻👌🏻 #togetheratEAS2022 #EASCongress2022
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@RGrueneis
Rebecca Grueneis
4 years
Excited to see my 1⃣st first-author paper out in @ATHjournal: 🧬 It's about the two faces of a well-known #lipoproteinA missense variant, rs41272110 (p.Thr3888Pro), and its SNP interaction with the KIV-2 4925G>A 🧬 Read more below ⬇️ and stay tuned for the twittorial 💬
@ATHjournal
Atherosclerosis
4 years
The 🆕 study by @RGrueneis &Coll emphasizes the complexity of the genetic regulation of Lp(a) and the importance to account for genetic subgroups in Lp(a) assoc studies https://t.co/tZlIztq7xd #CardioTwitter #EASCongress2022 @SilviaDiMaio4 @seppinho @lukfor @stncsn @KronenbergLab
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@johsr2
Johanna Schachtl-Riess
4 years
It still feels unreal but I am #PhDone 🙊 Thank you to everyone who celebrated with me yesterday including @KronenbergLab @azinkh96 @SilviaDiMaio4 @RGrueneis @stncsn @seppinho @lukfor @AmstlerStephan 🥳
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@azinkh96
azin kheirkhah
4 years
Excited to announce that our PCSK9 paper is now published @CJASN 🥳 @KronenbergLab
@asnpublications
ASN Publications
4 years
Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. This study found a significant association between higher PCSK9 concentrations and risk of cardiovascular disease https://t.co/FbrY2FGy3F @azinkh96
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@johsr2
Johanna Schachtl-Riess
4 years
Need to run a GWAS? Consider running it with the nf-gwas pipeline built by @lukfor and @seppinho! It has many advantages like an automated report 🥳 Head over to @seppinho for details 👇You never used the command line before? Here is my beginner's guide 🤓
genepi.github.io
nf-gwas: A nextflow pipeline to perform genome-wide association studies (GWAS) using regenie.
@seppinho
Sebastian Schönherr
4 years
⭐⭐ Pipeline release ⭐⭐ nf-gwas: A Nextflow pipeline to run genome wide association studies (GWAS). #gwas #Bioinformatics #nextflow 👇👇
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@lukfor
Lukas Forer
4 years
Making @nextflowio pipelines testable 🚀 @seppinho and I are happy to announce a first preview version of nf-test, a simple and elegant test framework to describe the expected behaviour of pipelines. https://t.co/EcSDYeopH8
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askimed.com
Askimed is the next-generation eCRF system designed for medical studies in the cloud.
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@johsr2
Johanna Schachtl-Riess
4 years
Excited that our paper is published in @jlipidres 🥳
@jlipidres
Journal of Lipid Research
4 years
"Lysis reagents, cell numbers, and calculation method influence high-throughput measurement of HDL-mediated #cholesterol efflux capacity" @imed_tweets @johsr2 @StefanCoassin @KronenbergLab https://t.co/RxfBtmJ5Pi
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@johsr2
Johanna Schachtl-Riess
5 years
So happy that our paper is now out there and big thanks to everyone #teamwork Head over to @StefanCoassin for a Tweetorial on our main findings
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@seppinho
Sebastian Schönherr
5 years
New work from our lab lead by @SilviaDiMaio4. UKBB data in action.
@JInternMed
JIM - Journal of Internal Medicine
5 years
Does #lipoproteinA modify #Covid19 risks? @KronenbergLab @SilviaDiMaio4 finds that high Lp(a) severely enhances ischemic heart disease risk in case of a COVID19 infection, but does not modify infection susceptibility and thrombosis risk in #UKBiobank. https://t.co/yPDHwS0tJq
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@statsgen
Emi Tanaka @[email protected]
8 years
ggplot2 has a lot (and I say A LOT) of theme customisation that I can't remember each time what the argument name was. I forgot that @rstudio can have addins and one of them makes the #ggplot theme customisation easier 🙂 #rstats
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