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Installation

  1. Install R (in case you don't have it already installed):

    Download and install R.

    You may want to install RStudio as well.

  2. Install devtools package in R (in case you don't have it already installed):

    install.packages("devtools")

    library(devtools)

  3. Install scDissector:

    install_github("effiken/scDissector")

Update

  1. Load devtools

library(devtools)

  1. Install the package as in (3) above

Running scDissector in R

library(scDissector)

run_scDissector()

or

run_scDissector(clustering_data_path =**["PATH"]**)

Loading the data prior to running scDissector

Loading the data prior to running scDissector is recommended:

ldm = load_scDissector_data(clustering_data_path=**["PATH"]**, model_name=[STRING], sample_names=[VECTOR_OF_STRINGS])

run_scDissector(preloaded_data = ldm, clustering_data_path = **["PATH"]**)

Loading Seurat Object and running scDissector

ldm=load_seurat_rds("[seurat_rds_file_path]",model_name,clustering_data_path=**["PATH"]**)

run_scDissector(preloaded_data = ldm, clustering_data_path = **["PATH"]**)

Loading MetcCell Object and running scDissector

ldm=load_metacell_clustering(mc_file,mat_file,model_name,clustering_data_path=["PATH"])`

run_scDissector(preloaded_data = ldm, clustering_data_path = **["PATH"]**)

scDissector-powered websites

https://scDissector.org/martin (Martin et al. Cell 2019)

About

scDissector is an exploratory data analysis tool for clustered single-cell RNA-seq data. The tool has been developed and implemented as R shiny app by Ephraim (Effi) Kenigsberg

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