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Updated: Nov 7, 2025

Isolation and Characterization of Single Cells from Zebrafish Embryos
Published on: March 12, 2016
Defining cell identity beyond the premise of differential gene expression
Hani Jieun Kim1,2,3, Patrick P L Tam4,5, Pengyi Yang6,7,8,9
1School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, 2006, Australia.
Abstract:
Identifying genes that define cell identity is a requisite step for characterising cell types and cell states and predicting cell fate choices. By far, the most widely used approach for this task is based on differential expression (DE) of genes, whereby the shift of mean expression are used as the primary statistics for identifying gene transcripts that are specific to cell types and states. While DE-based methods are useful for pinpointing genes that discriminate cell types, their reliance on measuring difference in mean expression may not reflect the biological attributes of cell identity genes. Here, we highlight the quest for non-DE methods and provide an overview of these methods and their applications to identify genes that define cell identity and functionality.
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