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Studying the molecular development of the human brain presents unique challenges for selecting the best data analysis approach. The rare and valuable nature of human postmortem brain samples, especially for studies examining development, means that those studies have small sample sizes (n) but often include measurements (p) for a large number of genes or proteins for every sample. Thus, most of those data sets have a structure that is p >> n, which introduces the problem of sparsity. Here wedoi:10.1101/2020.12.31.425014 fatcat:u3sbfqrdvfcnddg3wpb3nebgtm