Head of Statistical Genetics and Machine Learning at the Regeneron Genetics Center. Husband, Dad, Cycling addict. Stats/ML. Former Oxford Professor.
Joined March 2009
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Introducing a new method called REMETA from the Regeneron Genetics Center (RGC) @RegeneronDNA for meta-analysis of gene-based tests using summary statistics rgcgithub.github.io/remeta/ This is great work from Tyler Joseph. Pre-print is here
medrxiv.org/content/10.1101/…
Jonathan Marchini retweeted
Our paper in @NatureComms reveals how myostatin gene variants may protect muscle mass during weight loss. By studying 1M+ individuals, we found that rare MSTN variants are linked to increased skeletal muscle mass and reduced body fat.
Learn more: go.nature.com/3OyD0uo
Jonathan Marchini retweeted
We’re announcing a new collaboration with TriNetX to support Regeneron’s drug discovery and development and advance future digital health solutions. The work expands RGC’s EHR-linked database with access to ~300M de-identified patient records.
Read more: bit.ly/41bdUEE
Jonathan Marchini retweeted
Neurological disease risk is more common, and neurodegeneration may be detected earlier than we thought.
RGC analyzed 1M+ genomes, finding repeat expansions are more widespread, and that brain changes may begin years before symptoms appear.
Via @Nature: bit.ly/4tikaXH
Jonathan Marchini retweeted
Humans with function-disrupting variants in the myostatin gene (MSTN) have increased skeletal muscle mass and strength, and less adiposity
nature.com/articles/s41467-0…
Jonathan Marchini retweeted
It's such a painful process to upload summary statistics to GWAS catalog. Hey @GWASCatalog if you really care for open data sharing, then make the submission process simple. Get rid of globus personal connect.
The REMETA paper is now published in Nature Genetics. Great work from Tyler Joseph and team. See my previous post for a summary of the key properties of this approach xitter.cf/marchini/status/186685…
Exciting news from the RGC team!
Our latest paper in Nature Genetics introduces REMETA – a new tool for large-scale genetic meta-analysis.
Check out the full paper: go.nature.com/4oF5SOv
A thread listing 9 open positions at @RegeneronDNA. If you are at ASHG visit our booth to find out more
1. Pipeline Development careers.regeneron.com/en/job…
2. Proteomics Analysis/Methods careers.regeneron.com/en/job…
3. Applied Statistical Genetics careers.regeneron.com/en/job…
4. Translational Human Genetics (All Phenotypes) careers.regeneron.com/en/job…
5. Translational Genetics R-Code Developer careers.regeneron.com/en/job…
6. Clinical Informatics careers.regeneron.com/en/job…
7. Senior App Developer careers.regeneron.com/en/job…
8. Physician Scientist, Translational Genetics – Immunology careers.regeneron.com/en/job…
9. Physician Scientist, Obesity and Liver Disease Human Genetics careers.regeneron.com/en/job…
Some links to open positions in the Analytical Genetics group at @RegeneronDNA
Pipeline development careers.regeneron.com/en/job…
Proteomics analysis and methods careers.regeneron.com/en/job…
Applied statistical genetics careers.regeneron.com/en/job…
StatML and imaging careers.regeneron.com/en/job…
JOB ADVERT If you work in statistical genetics/machine learning/imaging and want to join the amazing RGC team @RegeneronDN working on some of the largest and most ancestrally diverse genetic datasets in the world, then check out this role careers.regeneron.com/en/job…
Jonathan Marchini retweeted
📣Today we announced that we intend to acquire @23andMe with plans to maintain their consumer genetics business and advance our shared goal of improving human health and wellness. bit.ly/43gI75D
Jonathan Marchini retweeted
REGENIE v4.1 now live!
github.com/rgcgithub/regenie…
Fourth, we have extended the approach to handle binary trait meta-analysis of gene-based tests with high case-control imbalance and show that this is well calibrated.
Finally, for ease of use we have developed this approach in an open-source software package called REMETA github.com/rgcgithub/remeta, that is designed to integrate seamlessly with the summary statistic output files from the REGENIE software rgcgithub.github.io/regenie/
Second, we have developed a compact per-chromosome binary file format for the LD files. The format handles both marginal and conditional testing scenarios and is indexed to allow fast access to the LD information of any gene.
REMETA solves these challenges and has several nice properties. Firstly, REMETA uses a single sparse covariance reference file per study that is rescaled for each phenotype using single variant summary statistics. This can be pre-calculated once, so it massively cuts down storage
