Seurat is an R package designed for QC, analysis, and exploration of single-cell RNA-seq data. Seurat aims to enable users to identify and interpret sources of heterogeneity from single-cell transcriptomic measurements, and to integrate diverse types of single-cell data.

Georges Pierre Seurat (UK: / ˈsɜːrɑː, - ə / SUR-ah, -⁠ə, US: / sʊˈrɑː / suu-RAH; [1][2][3][4][5]French: [ʒɔʁʒ pjɛʁ sœʁa]; [6] 2 December 1859 – 29 March 1891) was a French post-Impressionist artist. He devised the painting techniques known as chromoluminarism and pointillism and used conté crayon for drawings on paper with a rough surface.

A basic overview of Seurat that includes an introduction to common analytical workflows. An introduction to working with multi-modal datasets in Seurat. Learn to explore spatially-resolved transcriptomic data with examples from 10x Visium and Slide-seq v2.

Seurat is an R toolkit for single cell genomics, developed and maintained by the Satija Lab at NYGC. We are excited to release Seurat v5! This updates introduces new functionality for spatial, multimodal, and scalable single-cell analysis.

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

Seurat is an R package designed for QC, analysis, and exploration of single-cell RNA-seq data. Seurat aims to enable users to identify and interpret sources of heterogeneity from single-cell transcriptomic measurements, and to integrate diverse types of single-cell data. ---https://satijalab.org/seurat/ Advantages: beginning-to-end workflows

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

Seurat is an R toolkit for single cell genomics, developed and maintained by the Satija Lab at NYGC. We are excited to release an initial beta version of Seurat v5! This updates introduces new functionality for spatial, multimodal, and scalable single-cell analysis.