Fast GSEA implementation of the prerank algorithm. Use Loess interpolation of bimodal ES distribution for accurate p-value estimation.

Code and example data for running Consensus Non-negative Matrix Factorization on single-cell RNA-Seq data

A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.

Formalizing and benchmarking open problems in single-cell genomics

Formalizing and benchmarking open problems in single-cell genomics

Website hosted at https://openproblems.bio

Transformer for One-Stop Interpretable Cell-type Annotation

Deep count autoencoder for denoising scRNA-seq data

Benchmarking analysis of data integration tools

scikit-learn: machine learning in Python

A DSL for data-driven computational pipelines

Annotated data.

R toolkit for single cell genomics

Some simple command-line tools to clean-up / modify BibTeX files

Convert between AnnData and SingleCellExperiment

A collection of scripts and tools for loading, processing, and handling single cell data.

K-nearest neighbor smoothing for high-throughput single-cell RNA-Seq data

An implementation of MNN (Mutual Nearest Neighbors) correct in python.

Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics

Python package for dimension reduction of high-dimensional biological data.

Parameterized testing with any Python test framework

Run Rstudio Server in a conda environment

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 dr…