The shape of gene expression distributions matter: how incorporating distribution shape improves the interpretation of cancer transcriptomic data

Abstract excerpt

BACKGROUND: In genomics, we often assume that continuous data, such as gene expression, follow a specific kind of distribution. However we rarely stop to question the validity of this assumption, or consider how broadly applicable it may be to all genes that are in the transcriptome. Our study investigated the prevalence of a range of gene expression distributions in three different tumor types from the Cancer...

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