R toolkit for single cell genomics
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Updated
Oct 25, 2024 - R
R toolkit for single cell genomics
Deep probabilistic analysis of single-cell and spatial omics data
Reference mapping for single-cell genomics
starfish: unified pipelines for image-based transcriptomics
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
A tool for the unsupervised clustering of cells from single cell RNA-Seq experiments
This contains the dataset for comparing scRNA-seq analysis methods
A tool for unsupervised projection of single cell RNA-seq data
Tidy R query API for the harmonised and curated CELLxGENE single-cell atlas.
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.
Bayesian MCMC matrix factorization algorithm
Clone of the Bioconductor repository for the SingleCellExperiment package, see https://bioconductor.org/packages/devel/bioc/html/SingleCellExperiment.html for the official development version.
Rails/Docker application for the Broad Institute's single cell RNA-seq data portal
Clone of the Bioconductor repository for the DropletUtils package.
Tutorials, workflows, and convenience scripts for Single Cell Portal
Aligning gene expression trajectories of single-cell reference and query systems
Clone of the Bioconductor repository for the scran package.
A deep learning-based tool for alignment and integration of single cell genomic data across multiple datasets, species, conditions, batches
Access and Format Single-cell RNA-seq Datasets from Public Resources
This repository contains our CellTag workflow, as deployed in our 2018 Biddy et al., Nature paper.
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