R toolkit for single cell genomics
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Updated
Sep 30, 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
Tidy R query API for the harmonised and curated CELLxGENE single-cell atlas.
This contains the dataset for comparing scRNA-seq analysis methods
A tool for unsupervised projection of single cell RNA-seq data
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.
Clone of the Bioconductor repository for the SingleCellExperiment package, see https://bioconductor.org/packages/devel/bioc/html/SingleCellExperiment.html for the official development version.
Bayesian MCMC matrix factorization algorithm
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
Clone of the Bioconductor repository for the scran package.
Aligning gene expression trajectories of single-cell reference and query systems
A deep learning-based tool for alignment and integration of single cell genomic data across multiple datasets, species, conditions, batches
This repository contains our CellTag workflow, as deployed in our 2018 Biddy et al., Nature paper.
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