Topic: seurat Goto Github
Some thing interesting about seurat
Some thing interesting about seurat
seurat,extendSC adds functionalities to Seurat-based scRNA-Seq workflows.
User: basilkhuder
seurat,A guide to using a Seurat object in conjunction with RNA Velocity
User: basilkhuder
seurat,One liner tool to check the quality of your single-cell atlases.
Organization: becavin-lab
Home Page: https://checkatlas.readthedocs.io/en/latest/
seurat,RNA-seq, smRNA-seq, scRNA-seq & ATAC-seq workflows for @Cornell-Trex
User: bixbeta
seurat,Cell type annotation with local Large Language Models (LLMs) - Ensuring privacy and speed with extensive customized reports
Organization: celvoxes
Home Page: https://celvox.co
seurat,single cell and bulk RNASeq analysis scripts
User: cemalley
seurat,Inside Out Positional Tracking (6DoF) for GearVR/Cardboard/Daydream using ARCore v1.6.0
User: christophgeske
seurat,This repository contains R code, with which you can create 3D UMAP and tSNE plots of Seurat analyzed scRNAseq data
User: dragonmasterx87
seurat,Hello there! Some code on how to merge >2 Seurat objects and maintain object identity :)
User: dragonmasterx87
seurat,Generate high quality, publication ready visualizations for single cell transcriptomics data.
User: enblacar
Home Page: https://enblacar.github.io/SCpubr-book/
seurat,Review on Single Cell RNA-sequencing
User: gambalab
seurat,represent each cell in UMAP plots as a pie chart
User: harbourlab
seurat,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.
User: interactivereport
Home Page: https://cellxgenevip-ms.bxgenomics.com
seurat,SCISSORS builds upon the Louvain graph-based clustering in Seurat by optimizing parameter selection when reclustering cell groups, with an eye towards identifying rare cell types.
User: jr-leary7
seurat,R package: {rfca} Random forest-based cell annotation methods for scRNAseq analysis. {rfca} contains methods which identifies cell types using machine learning trained on a diversity of cell types, without the need for a labelled training dataset. It also allows you to train your own cell prediction models with your own labels (cell type, subtype, cell state, cluster number etc). This package is best suited for researchers who want to annotate their datasets in a quick and unbiased way, phenotype their datasets based on cell identity proportions, and discover common cell states across different datasets and disease models.
User: kimberle9
Home Page: https://kimberle9.github.io/rfca/articles/vignette.html
seurat,This project involves the Deconvolution (Digital flow-cytometry) of mice whole liver. ScRNA-Seq analysis was performed using Seurat R package, RNA-Seq pipeline was performed with HISAT2 (Alignment), HTSEQ (read count). Data normalization was performed, and the data was uploaded to CIBERSORTx to perform deconvolution analysis to identify the differences in cell type fractions between healthy samples and samples with Non-alcoholic Steatohepatitis (NASH).
User: kiteomoru
seurat,Scripts for sincle cell multiome analysis
User: kpatel427
seurat,add any phylogenetically based transcriptome evolutionary index (TEI) to single-cell data objects
User: kullrich
seurat,Transcriptomic analysis of the developing mouse habenula
User: liekevandehaar
seurat,Bring your single-cell data to life
Organization: lilab-bcb
Home Page: https://cirrocumulus.readthedocs.io/
seurat,Signac
User: mathewchamberlain
seurat,Single Cell RNA-seq Course
Organization: maxplanck-ie
seurat,Main projects during my current position in Petr Baranov Lab | Schepens Eye Research Institute, Mass General Hospital, Harvard Medical School
User: mcrewcow
seurat,Display gene expression along a given reduced dimension on a heatmap
User: milescsmith
seurat,R wrappers to connect Python dimensional reduction tools and single cell data objects (Seurat, SingleCellExperiment, etc...)
User: milescsmith
Home Page: https://milescsmith.github.io/ReductionWrappers/
seurat,A effort to collect all of the scRNA imputation methods and allow them to interface with scRNA-seq libraries (i. e. Seurat, SingleCellAssay, etc...)
User: milescsmith
seurat,Plot_ly-based plotting functions for use with Seurat objects
User: milescsmith
seurat,Comprehensive single-cell RNA seq analysis workflow: automatic cell labeling to drug discovery and repurposing. Work from UVA CPHG Miller Lab.
Organization: millerlab-cphg
seurat,NASQAR: A web-based platform for High-throughput sequencing data analysis and visualization
User: nasqar
Home Page: http://nasqar.abudhabi.nyu.edu
seurat,A web-based interactive (wizard style) application to perform a guided single-cell RNA-seq data analysis and clustering based on Seurat v3
User: nasqar
Home Page: http://nasqar.abudhabi.nyu.edu/SeuratV3Wizard
seurat,This is a web-based interactive (wizard style) application to perform a guided single-cell RNA-seq data analysis and clustering based on Seurat.
User: nasqar
Home Page: http://nasqar.abudhabi.nyu.edu
seurat,Bundle of Useful scRNA-seq Gating Tools Extending seuRat
User: nbroguiere
seurat,R package developed for single-cell RNA-seq analysis. It was designed using the Seurat framework, and offers existing and novel single-cell analytic work flows.
User: nmikolajewicz
seurat,A shiny app for single cell analysis based on Seurat
User: obenno
Home Page: https://obenno.github.io/scSpotlight/
seurat,.h5mu files interface for Seurat
Organization: pmbio
Home Page: https://pmbio.github.io/MuDataSeurat/
seurat,An example of immunopipe
User: pwwang
seurat,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.
User: qile0317
Home Page: https://qile0317.github.io/APackOfTheClones/
seurat,R package with collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.
User: samuel-marsh
Home Page: https://samuel-marsh.github.io/scCustomize/
seurat,Label elements within user drawn gates
User: stemangiola
seurat,Seurat meets tidyverse. The best of both worlds.
User: stemangiola
Home Page: https://stemangiola.github.io/tidyseurat/
seurat,scRNA-seq analysis 2022 workshop hosted by UMICH's CDS-SR
User: tstephie
seurat,Project includes an R pipeline created using Bioconductor and Seurat to preprocess and clean scRNA sequence datasets, perform Principal Component Analysis and identify anomalous differential gene expression.(In Progress)
User: vedant-s
seurat,Cluster-specific pseudo-bulk analysis of 10X single-cell RNA-seq data by connecting Seurat to the VBC RNA-seq pipeline.
User: vertesy
Home Page: https://vertesy.github.io/pseudoBulk
seurat,Multicore and utility functions for Seurat 2 & 3, using doMC / foreach packages.
User: vertesy
Home Page: https://vertesy.github.io/Seurat.multicore
seurat,Various utility functions for Seurat single-cell analysis
User: vertesy
Home Page: https://vertesy.github.io/Seurat.utils
seurat,An end-to-end Single-Cell Pipeline designed to facilitate comprehensive analysis and exploration of single-cell data.
User: zhanghao-njmu
Home Page: https://zhanghao-njmu.github.io/SCP/
seurat,Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
User: zjufanlab
Home Page: https://www.sciencedirect.com/science/article/pii/S2589004220300663
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