Deep probabilistic analysis of single-cell and spatial omics data

Inclusive model of expression dynamics with conventional or metabolic labeling based scRNA-seq / multiomics, vector field reconstruction and differential geometry analyses

A tool for semi-automatic cell type classification

Single cell perturbation prediction

muon is a multimodal omics Python framework

Clustering scRNAseq by genotypes

A wrapper for the kallisto | bustools workflow for single-cell RNA-seq pre-processing

A tool for semi-automatic cell type harmonization and integration

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.

Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network

Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.

Doublet detection in single-cell RNA-seq data.

ST Pipeline contains the tools and scripts needed to process and analyze the raw files generated with the Spatial Transcriptomics method in FASTQ format.

Demultiplexing pooled scRNA-seq data with or without genotype reference

Single-cell Hierarchical Poisson Factorization

Cellxgene Gateway allows you to use the Cellxgene Server provided by the Chan Zuckerberg Institute (https://github.com/chanzuckerberg/cellxgene) with multiple datasets.

A tool for fast and accurate summarizing of variant calling format (VCF) files

A Snakemake workflow and MrBiomics module for easy visualization of genome browser tracks of aligned BAM files (e.g., RNA-seq, ATAC-seq, scRNA-seq, ...) powered by the wrapper gtracks for the package pyGenomeTracks, and IGV-reports.

Automatic annotation of single-cell RNA-seq data from the literature

An unofficial demultiplexing strategy for SPLiT-seq RNA-Seq data