Discover theislab/geome Open Source project by Theis Lab (@theislab)

https://www.sc-best-practices.org

1,284

single-cell-best-practices

RNA Velocity generalized through dynamical modeling

666

scvelo

Reference mapping for single-cell genomics

335

scarches

CellRank: dynamics from multi-view single-cell data

310

cellrank

Benchmarking analysis of data integration tools

297

scib

Single cell perturbation prediction

276

scgen

Deep count autoencoder for denoising scRNA-seq data

247

dca

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

224

diffxpy

Mapping out the coarse-grained connectivity structures of complex manifolds.

174

paga

An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.

159

kBET

A Bayesian model for compositional single-cell data analysis

138

scCODA

data and model repository for single-cell data

136

sfaira

Models and datasets for perturbational single-cell omics

133

sc-pert

Convert between AnnData and SingleCellExperiment

122

anndata2ri

Electronic Health Record Analysis with Python.

111

ehrapy

Learning cell communication from spatial graphs of cells

109

ncem

Multi-omic single-cell optimal transport tools

moscot

Conversion between scRNA-seq objects

zellkonverter

chemCPA

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

Perturbation Analysis in the scverse ecosystem.

pertpy

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

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

destiny

scib-pipeline

Snakemake pipeline that works with the scIB package to benchmark data integration methods.

Conditional out-of-distribution prediction

trVAE

Additional code and analysis from the single-cell integration benchmarking project

scib-reproducibility

AutoGeneS

Tutorials for the SCOG Virtual Workshop ‘Spatial transcriptomics data analysis in Python’ - May 23-24, 2022

spatial_scog_workshop_2022

Dynamic models for single-cell RNA-seq time series.

pseudodynamics

tcellmatch

Reproducing result from the paper

scArches-reproducibility

scTab

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

deepflow

Fit generalized linear models in python.

batchglm

Generate cellular maps of differentiation manifolds with complex topologies.

graph_abstraction

DeepRT

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"

Covid_meta_analysis

Comprehensive pipeline for donor demultiplexing in single cell

hadge

Nextflow

scvelo_notebooks

Python package for Probe set selection for targeted spatial transcriptomics.

spapros

interactive_plotting

Learning motif contributions to cell transitions using sequence features and graphs.

mubind

Repository for Nicheformer: a foundation model for single-cell and spatial omics

nicheformer

scgen-reproducibility

GraphCompass: Graph Comparison Tools for Differential Analyses in Spatial Systems

graphcompass

multicpa

Conditional Autoencoders for Multiplexed Pixel Analysis

campa

CellRank's reproducibility repository.

cellrank_reproducibility

A guide to using the Python scRNA-seq analysis package Scanpy from R

scanpy-in-R

Collection of Sphinx extensions similar to (but more flexible than) numpydoc

scanpydoc

Reproducibility notebooks for scPoli

scPoli_reproduce

DeepCollisionalCrossSection

The code and analyses accompanying the manuscript “MetaMap: An atlas of metatranscriptomic reads in human disease-related RNA-seq data”.

MetaMap

scAnalysisTutorial

Multigrate: multiomic data integration for single-cell genomics

multigrate

A Shiny tool to define the cell-type of action by integrating single cell expression data with GWAS

GWAS-scRNAseq-Integration

superexacttestpy

Python implementation of the SuperExactTest package

ncem_tutorials

Cell type enrichment analysis using gene signatures and cluster markers

enrichment_analysis_celltype

moslin

Code, data and analysis for moslin.

diffxpy_tutorials

Tutorials for diffxpy.

cross_system_integration

expiMap_reproducibility

trvaep

GREAT algorithm in Python

greatpy

Sparsity-enforcing regularizer

PathReg

IMPA

ncem_benchmarks

squidpy_reproducibility

The best-practices workflow for single-cell RNA-seq analysis as determined by the community.

sc-best-practices-ce

tissue_tensorflow

Caching extension for Scanpy

scachepy

Notebooks for CPA figures

cpa-reproducibility

scCODA_reproducibility

This repo contains the analysis code describing the findings of Mayr_et_al

2020_Mayr

gastrulation_analysis

Reproducibility repo accompanying Strunz et al. "Alveolar regeneration through a Krt8+ transitional stem cell state that persists in human lung fibrosis". Nat Commun. 2020.

2019_Strunz

trVAE_reproducibility

Tutorials and examples for CellRank.

cellrank_notebooks

Analysis notebooks using the moscot package

moscot_notebooks

intercode

spapros-pipeline

ehrapy-tutorials

sfaira_tutorials

flowVI

flowVI: Flow Cytometry Variational Inference

2018_Angelidis

Reproducibility repo accompanying Angelidis et al. "An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics"

InterpretableAutoencoders

theislab repository overview

theislab.github.io

JavaScript

disent

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

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

ehrapy-datasets

Reproducibility repository for the Human Neural Organoid Atlas publication

neural_organoid_atlas

scatac_poisson_reproducibility

single-cell scanpy teaching

scanpy-demo-czbiohub

Finding branching events and tips in single cell differentiation trajectories

kbranches

jump-cpg0016-segmentation

Snakemake pipeline used to segment the cpg0016 dataset of the JUMP-Cell Painting Consortium

Code to reproduce results from the CellRank preprint

cellrank_reproducibility_preprint

Invariant Representation learning

inVAE

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

extended-single-cell-best-practices-container

Dockerfile

perturbation-metrics

repository for all LODE projects

100

LODE