GitHub

scNym - Semi-supervised adversarial neural networks for single cell classification

scNym is a neural network model for predicting cell types from single cell profiling data (e.g. scRNA-seq) and deriving cell type representations from these models. While cell type classification is ...
GitHub

ESCHR: A hyperparameter-randomized ensemble approach for robust clustering across diverse datasets

This example jupyter notebook on Google Colab provides a walkthrough of ESCHR analysis using an example scRNA-seq dataset. If you launch the notebook in Google Colab ...
C&EN

AllenDigger, a Tool for Spatial Expression Data Visualization, Spatial Heterogeneity Delineation, and Single-Cell Registration Based on the Allen Brain Atlas

State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology (Shanghai), Institute of Biophysics, Chinese Academy of Sciences, Beijing ...