Author: A.J.W. Haasnoot; M.W. Schilham; S.S.M. Kamphuis; P.C.E. Hissink Muller; A. Heiligenhaus; D. Foell; R.A. Ophoff; T.R.D.J. Radstake; A.I. Den Hollander; T.H.C.M. Reinards; S. Hiddingh; N. Schalij-Delfos; E.P.A.H. Hoppenreijs; M.A.J. van Rossum; C. Wouters; R.K. Saurenmann; N. Wulffraat; R. ten Cate; J.H. de Boer; S.L. Pulit; J.J.W. Kuiper
Title: An amino acid motif in HLA-DRß1 distinguishes patients with uveitis in juvenile idiopathic arthritis Document date: 2017_5_22
ID: 4it5c9n2_55
Snippet: Similar to the genome-wide association testing, additive logistic regression in the Phase 1 and Phase 2 data was first performed separately to check the overall behavior of the data. Then, the dosages were merged together, and logistic regression was performed on the dosage data using PLINK1.9, 30,31 correcting for the top 5 principal components, sex, and phase. To ensure that this mega-analysis approach was appropriate, we additionally performed.....
Document: Similar to the genome-wide association testing, additive logistic regression in the Phase 1 and Phase 2 data was first performed separately to check the overall behavior of the data. Then, the dosages were merged together, and logistic regression was performed on the dosage data using PLINK1.9, 30,31 correcting for the top 5 principal components, sex, and phase. To ensure that this mega-analysis approach was appropriate, we additionally performed an inverse variance-weighted meta-analysis of the two phases, and found that the results were highly concordant (Pearson's r of genome-wide betas = 0.95). To identify potential independent signals within the MHC, we performed a follow-up regression by conditioning on the top-most variant (Figure 1 ).
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