Purpose:To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3 RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes;	Conclusions: Clustering of time-series transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. Furthermore, single-cell trajectories reconstructed from both techniques reproduced expected differentiation dynamics. SOURCE: Alan Selewa (selewa@uchicago.edu) -  University of Chicago

Pluto Bioinformatics

GSE129096: Systematic comparison of single-cell and single-nucleus transcriptomes during cardiomyocyte differentiation