An Entropy Approach for Choosing Gene Expression Cutoff

Annotating cell types using single-cell transcriptome data usually requires binarizing the expression data to distinguish between the background noise vs. real expression or low expression vs. high expression cases. A common approach is choosing a "reasonable" cutoff value, but it remains unclear how to choose it. In this work, we describe a simple yet effective approach for finding this threshold value.