Author

Jennifer Sjaarda

SIB Swiss Institute of Bioinformatics

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· 2

Signature Assays, Organisms & Methods

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Research Focus:GWAS / association mapping· 2 Organism:human· 2 Approach:statistical model· 2 Assay:electronic health records· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Zoltán KutalikiD· 2 shared Jonathan SulciD· 1 shared

Activity by Year

2021-2022 · peak 1/yr

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2 top collaborators · 1 mutual co-author link

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2 shared papersGenetics

Zoltán KutalikORCID

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2 papers

Recent·Most cited

GeneticsbioRxivPreprintApr 22, 2022

The contribution of mate-choice, couple convergence and confounding to assortative mating

Jennifer Sjaarda, Zoltán Kutalik

This study uses Mendelian randomisation to investigate assortative mating in 51,664 UK Biobank couples, finding 54% of traits show causal partner relationships, with major confounders like income and health rating.

2 citations

humanelectronic health records

𝕏 PostBluesky

GeneticsbioRxivPreprintDec 8, 2021

Polynomial Mendelian Randomization reveals widespread non-linear causal effects in the UK Biobank

Jonathan Sulc, Jennifer Sjaarda, Zoltán Kutalik

This paper introduces PolyMR, a polynomial MR method that reveals non-linear causal effects in UK Biobank data, finding 84% of tested effects deviate from linearity.

2 citations

humanGWAS summary statistics

𝕏 PostBluesky