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Resolving treatment effects in single-cell RNA sequencing data

The treatment effects in single-cell RNA sequencing data do not form distinct clusters, making it difficult to identify differentially expressed genes between treatments. The current pipeline has been optimized, but the treatment effect remains 'blended' within cell-type clusters. The goal is to find a robust approach to identify differentially expressed genes between treatments despite the lack of clear treatment clustering.

Science, Biology, Cell Biology