Chunk #24 — Methods — Comorbidity and Trauma Study (CATS; N = 1,558) — Gene and SNP selection and gene-level testing

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Monoacylglycerol lipase (MGLL) polymorphism rs604300 interacts with childhood adversity to predict cannabis dependence symptoms and amygdala habituation: Evidence from an endocannabinoid system-level analysis.

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The gene-level empirical p-value was defined as the proportion of times the original Gene-Stat exceeded a permuted Gene-Stat. Bonferroni correction was then used to adjust for the 6 genes under study, with a final p-threshold p < .0083 (0.05/6). As a corollary to these gene-based analyses, individual SNPs were also tested for significance using a significance threshold of p < .0008 (α=.05/65 SNPs). All statistical analyses were coded in Python (v.2.7.6) using the Numerical Python (“NumPy”, v.1.7.1), StatsModels (v.0.5.0), and Python Data Analysis (“pandas”, v.0.12.0) libraries. Follow-up analyses of individual SNPs were conducted using the PROCESS (Hayes, 2013) and MODPROBE (Hayes & Matthes, 2009) macros in SPSS (v.22).