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I calculated LD score having fun with LDSC v1
0.0 in 1 centiMorgan windows around 13,307,412 non-singleton variants genotyped in 379 European individuals (CEU, FIN, GBR, IBS and TSI populations) in the phase 1 integrated release of the 1,000 Genomes Project 35 . For regression weights 13 , we restricted LD score calculation to SNPs included in both the GWAS sumap phase 3; for rg estimation in pairs of traits this was the intersection of SNPs for both traits and HapMap. Because population structure and confounding were highly controlled in the ALS summary statistics by the use of mixed linear model association tests, we constrained the LD score regression intercept to 1 for hS 2 estimation in ALS, and we also estimated hS 2 with a free intercept. For hS 2 estimation in all other traits and for rg estimation the intercept was a free parameter. We also estimated rg using ALS meta-analysis results 7 with free and constrained intercepts and with permuted data conserving population structure. Briefly, principal component analysis was carried out for each stratum using smartpca 36 and the three-dimensional space defined by principal components 1–3 was equally subdivided into 1,000 cubes. Within each cube, case–control labels were randomly swapped and association statistics were re-calculated for the entire stratum using logistic regression. Study-level P-values were then calculated using inverse variance weighted fixed effect meta-analysis implemented in METAL 7,12 . hS 2 was estimated for these meta-analysed permuted data using LD score regression (Supplementary Table 1).
We calculated PRS for 10,032 cases and 16,627 healthy controls in the ALS dataset (duplicate and suspected or confirmed related samples with the schizophrenia dataset removed), based on schizophrenia-associated alleles and effect sizes reported in the GWAS summary statistics for 6,843,674 SNPs included in both studies and in the phase 1 integrated release of the 1,000 Genomes Project 35 (imputation INFO score <0.3; minor allele frequency <0.01; A/T and G/C SNPs removed). SNPs were clumped in two rounds (physical distance threshold of 250 kb and a LD threshold (R 2 ) of>0.5 in the first round and a distance of 5,000 kb and LD threshold of >0.2 in the second round) using PLINK v1.90b3y, removing high-LD regions (Supplementary Table 4), resulting in a final set of 496,548 SNPs for PRS calculations. Odds ratios for autosomal SNPs reported in the schizophrenia summary statistics were log-converted to beta values and PRS were calculated using PLINK’s score function for twelve schizophrenia GWAS P-value thresholds (PT): 5 ? 10 ?8 , 5 ? 10 ?7 best hookup spots in Las Cruces , 5 ? 10 ?6 , 5 ? 10 ?5 , 5 ? 10 ?4 , 5 ? 10 ?3 , 0.05, 0.1, 0.2, 0.3, 0.4 and 0.5. A total of 100 principal components (PCs) were generated for the ALS sample using GCTA version 1.24.4. Using R version 3.2.2, a generalized linear model was applied to model the phenotype of individuals in the ALS dataset. PCs that had a significant effect on the phenotype (P<0.0005, Bonferroni-corrected for 100 PCs) were selected (PCs 1, 4, 5, 7, 8, 10, 11, 12, 14, 36, 49).
in which y is the phenotype on ALS dataset, ? ‘s the intercept of the model which have a hill ? for each and every changeable x.
A great Nagelkerke Roentgen dos worthy of are gotten for every single model and you may the newest baseline Nagelkerke Roentgen dos well worth are subtracted, resulting in a great ? informed me variance you to makes reference to the latest share regarding schizophrenia-founded PRS with the phenotype on ALS dataset. PRS investigation was also did in permuted situation–control research (step one,100000 permutations, saving case–handle proportion) to evaluate if the increased ? explained variance is a true signal with the phenotype. ? said variances and you can P-values had been averaged across the permutation analyses.
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