Bring your single-cell data to life
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Updated
Sep 18, 2024 - JavaScript
Bring your single-cell data to life
Single Cell RNA-seq Course
Label elements within user drawn gates
Analysis of Single-Cell RNA-seq Data to Evaluate the Efficacy of Hormonal Therapy in the Treatment of Endometriosis-Related Pain
Various utility functions for Seurat single-cell analysis
R package with collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.
Cell type annotation with local Large Language Models (LLMs) - Ensuring privacy and speed with extensive customized reports
Tools, wrappers, utilities, and resources for handling single-cell and spatial transcriptomics data
ThunderBio scRNA-seq pipeline
Generate high quality, publication ready visualizations for single cell transcriptomics data.
A shiny app for single cell analysis based on Seurat
R package for bundling Seurat Label Transfer objects, markdowns, and functions
An example of immunopipe
Seurat meets tidyverse. The best of both worlds.
Single-Cell RNA-seq analysis workflow for 10x Genomics data
Visualize clonal expansion via circle-packing. 'APackOfTheClones' extends 'scRepertoire' to produce a publication-ready visualization of clonal expansion at a single cell resolution, by representing expanded clones as differently sized circles.
Retinal ganglion cells regeneration in 2 days post optic nerve crush retina | Lydia Tai | Dong Feng Chen Lab collaboration | Schepens Eye Research Institute, Mass General Hospital, Harvard Medical School
R wrappers to connect Python dimensional reduction tools and single cell data objects (Seurat, SingleCellExperiment, etc...)
Enables cellxgene to generate violin, stacked violin, stacked bar, heatmap, volcano, embedding, dot, track, density, 2D density, sankey and dual-gene plot in high-resolution SVG/PNG format. It also performs differential gene expression analysis and provides a Command Line Interface (CLI) for advanced users to perform analysis using python and R.
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