Investigating skewness to understand gene expression heterogeneity in large patient cohorts

Abstract excerpt

BACKGROUND: Skewness is an under-utilized statistical measure that captures the degree of asymmetry in the distribution of any dataset. This study applied a new metric based on skewness to identify regulators or genes that have outlier expression in large patient cohorts. RESULTS: We investigated whether specific patterns of skewed expression were related to the enrichment of biological pathways or genomic...

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