Single Cell Network Profiler for Extraction of Systems Biology Patterns from scRNAseq Trajectories

Scellnetor Scellnetor is a novel clustering tool for scRNA-seq data that takes Scanpy generated AnnData objects in H5AD file-format as input. With Scellnetor you can compare two sets of cells that you manually select on one of your Scanpy-generated plots. The output will be connected components of genes where the genes are either differently or similarly expressed in the two sets. You can also do a clustering of a single set, where the genes in the connected components are similarly expressed. For every cluster, you get a plot showing mean gene expression and the genes’ 95 % confidence intervals and a table with statistically significant GO-terms.

For full documentation and the webservice, visit the Scellnetor page here.

Project Members

(Former group member)


(Grønning et al., 2020)
  1. Alexander GB Grønning, Mhaned Oubounyt, Kristiyan Kanev, Jesper Lund, Tim Kacprowski, Dietmar Zehn, Richard Röttger and Jan Baumbach. Comparative single-cell trajectory network enrichment identifies pseudo-temporal systems biology patterns in hematopoiesis and CD8 T-cell development. bioRxiv (2020). Link. An extended version of the manuscript is now published in Nature Computational Science.