First time using Scellnetor or need help?

Check out our documentation here.

Or check out our short screencast →→→
1
Upload Data
2
Select Plot
3
Select Trajectories
4
Select Parameter
5
Results

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.

Workflow of the webpage:
  1. Upload your data or try a test set
  2. Select the template-plot you want to use
  3. Draw trajectories or pick clusters
  4. Choose parameters for the constrained hierarchical clustering algorithm
  5. Inspect and download results
Enjoy.

You can upload your own AnnData object as a H5AD file.

You can upload your old data here as a ZIP file.


Tutorials

Alternatively, you can try some of the premade examples to give scellnetor a spin! The test dataset are designed for easy and quick overview of the features of Scellnetor!

Try single cells from a hematopoiesis study

The data is based on: Paul et al. (2015)

hej

Try single cells from a study on peripheral blood mononuclear cells

The data is based on: Clustering 3K PBMCs

Try single cells from another hematopoiesis study

The data is based on: DPT for hematopoiesis in mouse (Moignard et al., 2015)

Try single cells from a study on CD8+ T-cells in lung cancer

Test data is based on: Guo X et al. (2018)

hej

Try single cells from a study on dysfunctional T-cells in chronic infections

The data is based on: Kanev et al. (2019)