CleanFinder brings browser-based genome editing analysis to labs without coding

Genome editing lets scientists rewrite DNA, the instruction manual inside every living cell, with a precision that was unthinkable a generation ago. Technologies such as CRISPR have made this almost ...
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 ...
Europe PMC

SCANPY: large-scale single-cell gene expression data analysis.

SCANPY is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential ...