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Megabase-scale somatic copy number variants (CNVs) alter allelic diversity in a subset of human neocortical neurons. Reported frequencies of CNV neurons range from ~5% of neurons in some individuals to greater than 30% in other individuals. Genome-wide and familial studies implicitly assume a constant brain genome when assessing the genetic risk architecture of neurological disease, thus it is critical to determine whether divergent reports of CNV neuron frequency reflect normal individual variation or technical differences between approaches. We generated a new dataset of over 800 human neurons from 5 neurotypical individuals and developed a computational approach that measures single cell library quality based on Bayesian Information Criterion and identifies integer-like variant segments from population-level statistics. A brain CNV atlas was assembled using our new dataset and published data from 10 additional neurotypical individuals. This atlas reveals that the frequency of neocortical CNV neurons varies widely among individuals, but that this variability is not readily accounted for by tissue quality or CNV detection approach. Rather, the age of the individual is anti-correlated with CNV neuron frequency. Fewer CNV neurons are observed in aged individuals than young individuals.

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