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consensus-clustering-evaluation

Evaluation pipeline for the multi-resolution consensus clustering project

countae

Deep count autoencoder for denoising scRNA-seq data

covid-perturbation

covid_macrophages_integration

scRNA-seq data integration from "SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis".

covid_meta_analysis

Analysis notebooks for the Covid-19 meta analysis that accompanies the Nature Medicine publication "Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics"

cpa

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.

cpa-reproducibility

Notebooks for CPA figures

dali

Deep Autoencoder Feature LearnIng

dca

Deep count autoencoder for denoising scRNA-seq data

deepcollisionalcrosssection

deepflow

This code contains the neural network implementation from the nature communication manuscript NCOMMS-16-25447A.

deeprt

destiny

R package for single cell and other data analysis using diffusion maps

diffusion_model_sc

diffxpy

Differential expression analysis for single-cell RNA-seq data.

diffxpy_tutorials

Tutorials for diffxpy.

disent

Out-of-distribution prediction with disentangled representations for single-cell RNA sequencing data

edgepy

ehrapy

Electronic Health Record Analysis with Python.

ehrapy-cli

Command line interface of ehrapy

ehrapy-datasets

A collection of scripts to generate AnnData objects of EHR datasets for ehrapy

ehrapy-site

ehrapy-tutorials

Tutorials for ehrapy

enrichment_analysis_celltype

Cell type enrichment analysis using gene signatures and cluster markers

epicardiods_analysis

expimap_reproducibility

extended-single-cell-best-practices-container

Hosting the container for the extended single-cell best-practices book

feature-attribution-sc

filtration_curves

Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'

flexible_priors

Using a VAE model with flexible priors for modelling scRNA-seq data