Topological Data Analysis of In Vitro Motor Neuron Differentiation from mESCs

The directed differentiation of murine embryonic stem cells into motor neurons enables in vitro modeling of neurodegenerative diseases and rational approaches to regenerative therapies. We differentiated murine embryonic stem cells into motor neurons and, using modifications to the CEL-Seq approach, we generated libraries from 2,744 single cells sampled across days two through six of differentiation1. These time points span the transition from pluripotency to post-mitotic fate. Single cell RNA-Seq read counts were analyzed using the scTDA method, that builds upon developments in topological data analysis. Through this webpage you can explore some of the results of this analysis.


These two figures contain topological representations of the data from the pilot experiment (440 cells) and the main experiment (2,304 cells), colored by time point. Each node represents a set of single cells with related transcriptional programs. The same cell may appear in several nodes. Nodes that have one or more cells in common are connected through an edge. Hence, connected nodes are also transcriptionally related.


Using the following form, you can color the above topological representations by expression of any gene (red: high values; blue: low values). Several statistics associated to the gene are also displayed. See [1] for more details on the experimental setting, analysis and statistics.

1 Single-cell topological RNA-seq analysis reveals insights into cellular differentiation and development.
Abbas H. Rizvi*, Pablo Camara*, Elena K. Kandror, Thomas J. Roberts, Ira Scheiren, Tom Maniatis, and Raul Rabadan.
Nature Biotechnology. 2017 Jun;35(6):551-560. doi: 10.1038/nbt.3854..
* These authors have contributed equally to this work.

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