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Chunk #5 — Materials and methods — Samples — RNA-seq

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Genome- and transcriptome-wide splicing associations with alcohol use disorder.
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We used the same publicly available data source of human post-mortem brain samples as Van Booven et al.7, which were collected from the New South Wales Brain Tissue Resource Center. Van Booven et al.7 also performed differential splicing, but they used different methods, included individuals from disparate ancestral backgrounds, and did not investigate genetic links with splicing. Using 56 Caucasian individuals14 (Supplementary Fig. S1), our study explored the possible genetic links of AUD-related splicing in the brain. Note, we derived genome-wide DNA variant information from RNA-seq brain data. Principal components analysis showed that individuals from the RNA-seq data were genetically homogenous, but did not cluster with the ancestral populations in 1000 Genomes reference samples—likely due to differences in data types (RNA-seq vs. GWAS). Still, systematic differences were observed between the ancestral clustering of RNA-seq data with genomic reference samples, which decreases the portability of polygenic score analyses. Of the human brain samples 23.22% were female and the average age was 57.34 (s.d. = 8.91, range = 40–73; see Table 1). AUD was defined as a diagnosis of either DSM-IV alcohol