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Paper out now: GRN inference with popInfer

popInfer: a novel method for the inference of gene regulatory networks governing dynamic cell state transitions is published now in iScience. popInfer learns cell type-specific networks governing dynamic transitions by learning a joint regression model using both RNA-seq and ATAC-seq signals from the same single cells. Applied to a multiomic dataset on hematopoietic stem cell aging, popInfer discovered a mutual inhibition network between Mecom and Cdk6 that controlled stem cell quiescence.

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