Nina Mars (@ninajmars) 's Twitter Profile
Nina Mars

@ninajmars

MD, PhD. Enjoying being in the interface of #medicine and #statistics

Group leader @FIMM_UH and visiting researcher @broadinstitute

ID: 763794134436048896

calendar_today11-08-2016 17:48:07

525 Tweet

722 Takipçi

358 Takip Edilen

Michael White (@mwclimatesci) 's Twitter Profile Photo

I’ve handled the review of > 1000 papers at @nature. Over time, you notice aspects of presentation on which reviewers tend to comment. In the interests of minimizing hassles during review, I offer the following suggestions (a bit targeted to climate papers).

Sasha Gusev (@sashagusevposts) 's Twitter Profile Photo

A six feature logistic LASSO model predicts immunotherapy response better than prior Machine Learning methods. A good reminder that bigger isn't always better and treatment history matters a lot! [Chang et al. Nature Cancer nature.com/articles/s4301…]

A six feature logistic LASSO model predicts immunotherapy response better than prior Machine Learning methods. A good reminder that bigger isn't always better and treatment history matters a lot!

[Chang et al. Nature Cancer  nature.com/articles/s4301…]
Brooke N. Wolford, PhD (@bnwolford) 's Twitter Profile Photo

Really proud of this team effort with Brad Jermy, Kristi Läll & the rest of the INTERVENE team. nature.com/articles/s4146… We hope our framework will enable risk-based prevention and screening & bring polygenic scores into more precision medicine approaches.

Aoxing Liu (@aoxing2) 's Twitter Profile Photo

New out in Nature!! With age, women can lose one X chromosome in their leukocytes. What’s the cause/consequence? How does it differ from the loss of the Y chromosome in men? nature.com/articles/s4158… Broad Institute FinnGen FIMM HelsinkiUni National Cancer Institute Cambridge University

Sasha Gusev (@sashagusevposts) 's Twitter Profile Photo

Really nice method for computing context specific polygenic score uncertainty. PRS methods are so far ahead of most clinical scores on this point. nature.com/articles/s4158…

Andrea ganna (@andganna) 's Twitter Profile Photo

Q: Is the variability in polygenic score performance larger between biobanks or between the methods used to build the scores? A: Between biobanks! Phenotype harmonization remains key for polygenic scores transferablity Great project led by Remo Monti Christoph Lippert Lisa Eick

Veera Rajagopal  (@doctorveera) 's Twitter Profile Photo

Comparison of imputation performance for rare variants between three reference panels (HRC, GEL (Genomics England), and TOPMed) in continental ancestries. While TOPMed is best (or as good as GEL) for European, African and admixed American ancestries, GEL panel is great for South

Comparison of imputation performance for rare variants between three reference panels (HRC, GEL (Genomics England), and TOPMed) in continental ancestries. While TOPMed is best (or as good as GEL) for European, African and admixed American ancestries, GEL panel is great for South
Marios Georgakis (@mariosgeorgakis) 's Twitter Profile Photo

I'm often asked about the latest GWAS datasets for different cardiovascular traits🧬 🔗This is my list with links to the most recent and largest publicly available GWAS summary statistics for cardiometabolic traits❗️ docs.google.com/spreadsheets/d…

Marios Georgakis (@mariosgeorgakis) 's Twitter Profile Photo

No matter how much we search, genetics continues to hide gems🧬 In N=174,329 postmenopausal women homozygosity for a stop-gain variant in CCDC201 leads to menopause 9 years earlier! 👉OR=35 for menopause <45 y 👉OR=27 for menopause <40 y nature.com/articles/s4158…

No matter how much we search, genetics continues to hide gems🧬

In N=174,329 postmenopausal women homozygosity for a stop-gain variant in CCDC201 leads to menopause 9 years earlier!

👉OR=35 for menopause &lt;45 y
👉OR=27 for menopause &lt;40 y

nature.com/articles/s4158…
Samuel Hume (@drsamuelbhume) 's Twitter Profile Photo

4. Most type 1, and some type 2 diabetics, are dependent on daily insulin injections to control their blood sugar These phase 3 trials for daily (degludec) vs. weekly (efsitora) insulin, in type 1 (left) and 2 (right) diabetes, found that once-weekly insulin was just as good as

4. Most type 1, and some type 2 diabetics, are dependent on daily insulin injections to control their blood sugar 

These phase 3 trials for daily (degludec) vs. weekly (efsitora) insulin, in type 1 (left) and 2 (right) diabetes, found that once-weekly insulin was just as good as
FIMM HelsinkiUni (@fimm_uh) 's Twitter Profile Photo

Warm welcome to the Harvest time at FIMM seminar! FIMM Director Samuli Ripatti and new FIMM-EMBL Group Leaders will present their plans for the near future. 📅Wednesday Oct 30 at 13:15-15:00 🏢Biomedicum Helsinki, Lecture Hall 1 More information and registration: lyyti.fi/reg/FIMM_harve…

Warm welcome to the Harvest time at FIMM seminar!
FIMM Director <a href="/samrip/">Samuli Ripatti</a> and new FIMM-EMBL Group Leaders will present their plans for the near future.
📅Wednesday Oct 30 at 13:15-15:00
🏢Biomedicum Helsinki, Lecture Hall 1
More information and registration: lyyti.fi/reg/FIMM_harve…
FinnGen (@finngen_fi) 's Twitter Profile Photo

Last autumn FinnGen hit its target of sampling close to 10% of the Finnish population with more than 500,000 participants. We are happy to announce that the results based on the full cohort are now publicly available for the whole research community: finngen.fi/en/results-bas…

Last autumn FinnGen hit its target of sampling close to 10% of the Finnish population with more than 500,000 participants. We are happy to announce that the results based on the full cohort are now publicly available for the whole research community:
finngen.fi/en/results-bas…
Nikhil Milind (@thenikhilmilind) 's Twitter Profile Photo

For many traits there is a correlation between the number of duplications or loss-of-function (LoF) mutations someone carries, and their phenotype. Curiously, for most traits, these effects are aligned in the SAME direction. Why?

For many traits there is a correlation between the number of duplications or loss-of-function (LoF) mutations someone carries, and their phenotype. Curiously, for most traits, these effects are aligned in the SAME direction. Why?
Heidi Rehm (@heidirehm) 's Twitter Profile Photo

Forthcoming guidance will recommend labs report VUS subclasses. We share experience of 4 labs including rates of reclassification of VUS subclasses. By highlighting VUS-high and downplaying VUS-low, this will be game-changing for dx genetic testing. buff.ly/3Cpx5RL

Forthcoming guidance will recommend labs report VUS subclasses. We share experience of 4 labs including rates of reclassification of VUS subclasses. By highlighting VUS-high and downplaying VUS-low, this will be game-changing for dx genetic testing. buff.ly/3Cpx5RL
FinnGen (@finngen_fi) 's Twitter Profile Photo

A FinnGen-based study led by researchers FIMM HelsinkiUni has discovered a genetic defect in the TBPL2 gene that affects the maturation of oocytes, leading to infertility in women who have inherited the non-functional form of the gene from both parents. helsinki.fi/en/news/genes/…

Veera Rajagopal  (@doctorveera) 's Twitter Profile Photo

Comparison of pathway-specific polygenic risk score for type 2 diabetes between Europeans (purple) vs South Asians (green; Pakistanis & Bangladeshis). While obesity risk variants are enriched in Europeans, lipodystrophy risk variants are enriched in South Asians, explaining the

Comparison of pathway-specific polygenic risk score for  type 2 diabetes between Europeans (purple) vs South Asians (green; Pakistanis &amp; Bangladeshis). While obesity risk variants are enriched in Europeans, lipodystrophy risk variants are enriched in South Asians, explaining the
FinnGen (@finngen_fi) 's Twitter Profile Photo

Million Veteran Program & FinnGen teams are pleased to release v1 meta-analysis of MVP, FinnGen and UKBB GWAS data. This first version includes ~300 binary disease definitions across >1.5 M individuals. Browse scans at: mvp-ukbb.finngen.fi

Million Veteran Program &amp; FinnGen teams are pleased to release v1 meta-analysis of MVP, FinnGen and UKBB GWAS data.  This first version includes ~300 binary disease definitions across &gt;1.5 M individuals.  Browse scans at:
mvp-ukbb.finngen.fi