Harm-Jan Westra on Muck Rack

Harm-Jan Westra

As seen in: Nature, Genome Biology, Genome Medicine
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Articles

Non-coding autoimmune risk variant defines role for ICOS in T peripheral helper cell development - Nature Communications

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By Qiang Wang, Nicolaj S Hackert, Jeffrey A Sparks, Roxane Darbousset, Raquel Laza-Briviesca, Harm-Jan Westra, Matthew T Weirauch, Deepak Rao
| Nature Verified
Abstract Fine-mapping and functional studies implicate rs117701653, a non-coding single nucleotide polymorphism in the CD28/CTLA4/ICOS locus, as a risk variant for rheumatoid arthritis and type 1 diabetes.
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PICALO: principal interaction component analysis for the identification of discrete technical, cell-type, and environmental factors that mediate eQTLs | Genome Biology | Full Text

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By Martijn Vochteloo, Patrick Deelen, Ellen A. Tsai, Heiko Runz, Sergio Andreu-Sánchez, Jingyuan Fu, Alexandra Zhernakova, Harm-Jan Westra, Lude Franke, Britt Vink
| Genome Biology Verified
PICALO is an EM-based algorithm for the identification of known and unknown contexts that influence the regulatory effect of genetic variants on gene expression. PICALO takes as input a set of eQTLs and their corresponding expression and genotype data, as well as a set of starting positions (e.g., potential context components). Optional arguments allow for the correction of technical covariates both with and without an interaction term.
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KidneyNetwork: using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease - European Journal of Human Genetics

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By Floranne Boulogne, Niek de Klein, Harm-Jan Westra, Patrick Deelen
| Nature Verified
Abstract Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases.
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