Author

Reedik Magi

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetics· 3

Signature Assays, Organisms & Methods

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Research Focus:GWAS / association mapping· 3 Organism:human· 3 Approach:statistical model· 3 Research Focus:fine-mapping· 1 Assay:GWAS summary statistics· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Andres MetspaluiD· 3 shared Krista FischeriD· 2 shared Mart KalsiD· 2 shared Pradeep NatarajaniD· 2 shared Sekar KathiresaniD· 2 shared Tonu EskoiD· 2 shared Aarno Palotie· 1 shared Alex Bloemendal· 1 shared

Activity by Year

2016-2016 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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3 shared papersGenetics

Andres MetspaluORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms

Michael Guo, Satish K Nandakumar, Jacob C Ulirsch, Seyedeh Maryam Zekavat, Jason D Buenrostro, Pradeep Natarajan, Rany Salem, Roberto Chiarle, Mario Mitt, Mart Kals, Kalle Parn, Krista Fischer, Lili Milani, Reedik Magi, Priit Palta, , Vijay G Sankaran

This study uses genome sequencing and epigenomic data to identify genetic variants influencing blood cell traits and uncover regulatory mechanisms in hematopoiesis.

Proceedings of the National Academy of Sciences · Dec 28, 2016Peer-reviewedGenetics

Ultra-rare disruptive and damaging mutations influence educational attainment in the general population

Andrea Ganna, Giulio Genovese, Daniel P Howrigan, Andrea Byrnes, Mitja Kurki, Seyedeh M Zekavat, Christopher W Whelan, Robert E Handsaker, Mart Kals, Alex Bloemendal, Jonathan M Bloom, Jacqueline I Goldstein, Timothy Poterba, Cotton Seed, Michel G Nivard, , Benjamin M Neale

This study finds that ultra-rare disruptive variants in highly constrained genes are associated with reduced educational attainment in the general population.

bioRxiv · Jun 7, 2016Genetics

Personalized Risk Prediction for Type 2 Diabetes: the Potential of Genetic Risk Scores

Kristi Lall, Reedik Magi, Andrew Morris, Andres Metspalu, Krista Fischer

This study develops a genetic risk score for Type 2 Diabetes prediction and finds it improves risk prediction accuracy when added to existing models.

bioRxiv · Feb 29, 2016Genetics