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Stochastic Single Cell RNA Velocity
Single-Cell Analysis in Python. Scales to >1M cells.
Single cell best practices tutorial case study for the paper:Luecken and Theis, "Best practices in single-cell RNA-seq analysis: a tutorial"
Fit over-determined GLMs.
Differential expression analysis for single-cell RNA-seq data.
Tutorials for diffxpy.
Deep count autoencoder for denoising scRNA-seq data
Software required for Bart-Seq technology – a cheap technology to analyze (single) cells using forward and reverse barcoding for target genes
Scanpy use cases.
Mapping topologies of complex manifolds.
A Shiny tool to define the cell-type of action by integrating single cell expression data with GWAS
MetaMap - This repository describes the code and analyses accompanying the "MetaMap: An atlas of metatranscriptomic reads in human disease-related RNA-seq data" manuscript.
Dynamic models for single-cell RNA-seq time series.
An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.
This interactive web tool facilitates exploration of the MetaMap resource (Simon et al. bioRxiv). In this large scale re-analysis raw RNA-seq data from over 400 studies relevant to human disease were screened for microbial and viral reads.
R package for single cell and other data analysis using diffusion maps
Generate cellular maps of differentiation manifolds with complex topologies.
Vignette Engine wrapping Jupyter Notebooks
Use cases for anndata.
This code contains the neural network implementation from the nature communication manuscript NCOMMS-16-25447A.
Cell type enrichment analysis using gene signatures and cluster markers
Differential expression analysis for single-cell RNA-seq data
theislab repository overview
Finding branching events and tips in single cell differentiation trajectories