Mathematics improve single-cell analysis

More than 40% of all genes in the experiment were significantly correlated to a small set of known cell-cycle markers - Graphic: Florian BA1 4ttner A new computational approach allows to account for confounding factors and hidden biological processes in the analysis of single-cell RNA sequence data. Using this method, individual subpopulations and cell types can be identified within heterogeneous cell populations and can be determined more precisely.

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