R-universe search: topic:seurat

Showing 8 of total 8 results (show query)

stemangiola

tidyseurat:Brings Seurat to the Tidyverse

It creates an invisible layer that allow to see the 'Seurat' object as tibble and interact seamlessly with the tidyverse.

Maintained by Stefano Mangiola. Last updated 8 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics dplyr ggplot2 pca purrr sct seurat single-cell single-cell-rna-seq tibble tidyr tidyverse transcripts tsne umap

159 stars 9.48 score 398 scripts 1 dependents

enblacar

SCpubr:Generate Publication Ready Visualizations of Single Cell Transcriptomics Data

A system that provides a streamlined way of generating publication ready plots for known Single-Cell transcriptomics data in a “publication ready” format. This is, the goal is to automatically generate plots with the highest quality possible, that can be used right away or with minimal modifications for a research article.

Maintained by Enrique Blanco-Carmona. Last updated 1 months ago.

software singlecell visualization data-visualization ggplot2 publication-quality-plots seurat single-cell single-cell-genomics single-cell-rna-seq

178 stars 8.71 score 194 scripts

samuel-marsh

scCustomize:Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing

Collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using 'R'. 'scCustomize' aims to provide 1) Customized visualizations for aid in ease of use and to create more aesthetic and functional visuals. 2) Improve speed/reproducibility of common tasks/pieces of code in scRNA-seq analysis with a single or group of functions. For citation please use: Marsh SE (2021) "Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing" <doi:10.5281/zenodo.5706430> RRID:SCR_024675.

Maintained by Samuel Marsh. Last updated 3 months ago.

customization ggplot2 scrna-seq seurat single-cell single-cell-genomics single-cell-rna-seq visualization

246 stars 8.45 score 1.1k scripts

zjufanlab

scCATCH:Single Cell Cluster-Based Annotation Toolkit for Cellular Heterogeneity

An automatic cluster-based annotation pipeline based on evidence-based score by matching the marker genes with known cell markers in tissue-specific cell taxonomy reference database for single-cell RNA-seq data. See Shao X, et al (2020) <doi:10.1016/j.isci.2020.100882> for more details.

Maintained by Xin Shao. Last updated 2 years ago.

cell-markers cluster-annotation marker-genes rna-seq sequencing seurat single-cell transcriptome transcriptomics

226 stars 7.13 score 75 scripts

stemangiola

tidygate:Interactively Gate Points

Interactively gate points on a scatter plot. Interactively drawn gates are recorded and can be applied programmatically to reproduce results exactly. Programmatic gating is based on the package gatepoints by Wajid Jawaid (who is also an author of this package).

Maintained by Stefano Mangiola. Last updated 6 months ago.

assaydomain infrastructure clustering datavis dataviz dplyr drawing facs gate ggplot2 interactive pipe programmatic seurat single-cell single-cell-rna-seq tibble tidy-data tidyverse

23 stars 6.89 score 14 scripts 1 dependents

mathewchamberlain

SignacX:Cell Type Identification and Discovery from Single Cell Gene Expression Data

An implementation of neural networks trained with flow-sorted gene expression data to classify cellular phenotypes in single cell RNA-sequencing data. See Chamberlain M et al. (2021) <doi:10.1101/2021.02.01.429207> for more details.

Maintained by Mathew Chamberlain. Last updated 2 years ago.

cellular-phenotypes seurat single-cell-rna-seq

24 stars 6.46 score 34 scripts

qile0317

APackOfTheClones:Visualization of Clonal Expansion for Single Cell Immune Profiles

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. The method was originally implemented by Murray Christian and Ben Murrell in the following immunology study: Ma et al. (2021) <doi:10.1126/sciimmunol.abg6356>.

Maintained by Qile Yang. Last updated 4 months ago.

clonal-analysis immune-repertoire immune-system scrna-seq scrnaseq seurat single-cell single-cell-genomics cpp

15 stars 6.45 score 15 scripts

obenno

scSpotlight:A Single Cell Analysis Shiny App

A single cell analysis (viewer) app based on Seurat.

Maintained by Zhixia Xiao. Last updated 7 months ago.

seurat shiny-apps single-cell

2 stars 2.78 score