Computational protocol: The genetic architecture of pediatric cognitive abilities in the Philadelphia Neurodevelopmental Cohort

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Protocol publication

[…] This study employed genome wide complex trait analysis (GCTA) to estimate the fractional contribution of common SNPs to phenotypic variation in cognitive ability in the general population. One can reduce bias in values estimated through GCTA by minimizing ancestral heterogeneity in the sample (, ). As the PNC cohort was drawn from a diverse United States urban population, these analyses were limited at the outset to the subset of participants who identified themselves as white non-hispanic (WNH; n=5,141). All samples were genotyped on one of three Illumina arrays: the HumanHap550, HumanHap610, or OmniExpress v2. Within the self-described WNH group, population outliers were further excluded based on directly genotyped SNP data, prior to imputation. Data were cleaned using a standard approach ()(), which reduced the sample by 584 individuals. Over half (62%) of these individuals were excluded for excess relatedness (the PNC included siblings). We conducted a principal components analysis in PLINK () () which identified 527 individuals with outlying ethnicity, who were subsequently removed. An additional 341 individuals were removed in further phenotypic and genotypic exclusions, described below, resulting in a final analytic sample of 3,689 individuals.The genotype data were imputed in a separate phase of the study at CHOP. Unobserved genotypes from each chip set were imputed using the IMPUTE2 package and the reference haplotypes in Phase I of the 1000 genomes data (June 2011 release) that included approximately 37,138,905 variants from 1,094 individuals from Africa, Asia, Europe and the Americas. Methodological details regarding the imputation are provided in the . The imputed genotype data were used in the GCTA analyses. […]

Pipeline specifications

Software tools GCTA, PLINK, IMPUTE
Application GWAS
Organisms Homo sapiens