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D6.3v1: Genome Wide Association Study Workflows v1

Kristina Hettne; Peter Henneman; Harish Dharuri; Eleni Mina; Marco Roos

This document describes the workflows developed at the Human Genetics Department of the Leiden University Medical Centre (HG-LUMC) for interpreting results from genomics studies.

The main goal of this deliverable is to produce workflows. Preservation aspects have been preliminarily explored and will be explored in more detail in future versions (D6.3v2/v3).

Case studies at the HG-LUMC provide data to populate the models and software for Research Objects (ROs) that are under development in Wf4Ever, in particular a genotype-phenotype study for unravelling Metabolic Syndrome (MetS) and a study investigating the role of epiGenetics in Huntington's Disease.

Workflows form a crucial part of the data to populate the RO models and software in Wf4Ever, and the HG-LUMC is committed to producing such workflows.

In this document, we describe the genomics-related workflows developed at the HG-LUMC, namely workflows for interpreting Genome Wide Association Study (GWAS) data and epiGenetics workflows for Huntington's Disease.

Finally, we characterize the workflows developed at the HG-LUMC according to current state of workflow preservation and the external resources that they are dependent upon.

Wf4Ever Deliverable. Identifier: oai:repo.wf4ever-project.org:31
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  • P. Henneman, Y.S. Aulchenko, R.R. Frants, K.W. van Dijk, B.A. Oostra, and C.M. van Duijn, "Prevalence and heritability of the metabolic syndrome and its individual components in a Dutch isolate: the Erasmus Rucphen Family study," Journal of Medical Genetics, vol. 45, Sep. 2008, pp. 572-577.

  • R. Jelier, P.A.C. 't Hoen, E. Sterrenburg, J.T. den Dunnen, G.J. van Ommen, J.A. Kors, B. Mons. "Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease". BMC Bioinformatics, vol. 9, 2008 p. 291.

  • R. Jelier, J.J. Goeman, K.M. Hettne, M.J. Schuemie, J.T. den Dunnen, and P.A.C. 't Hoen, "Literature-aided interpretation of gene expression data with the weighted global test," Briefings in Bioinformatics, vol. 12, 2011, p. 518-29.

  • R. Jelier, G. Jenster, L.C. Dorssers, B.J. Wouters, P.J. Hendriksen, B. Mons, R. Delwel, and J.A. Kors, "Text-derived concept profiles support assessment of DNA microarray data for acute myeloid leukemia and for androgen receptor stimulation," BMC bioinformatics, vol. 8, 2007, p. 14.

  • R. Jelier, M.J. Schuemie, A. Veldhoven, L.C. Dorssers, G. Jenster, J.A. Kors. "Anni 2.0: a multipurpose text-mining tool for the life sciences". Genome Biology, vol. 9, 2008, p. R96

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