README.md

In WubingZhang/scAnalyzer: Integrative analysis pipeline for analyzing single-cell RNA-seq data

scAnalyzer

This package provides an integrative analysis pipeline for single-cell RNA-seq data. It implements methods to perform quality control (QC), doublets removal, normalization, clustering, cell type annotation, malignant cell identification, immature cancer cell identification and data visualization.

Installation

Installing the package in a fresh R environment may take a long time.

Prerequisites

To install scAnalyzer, you have to first install conda following the document (https://docs.conda.io/projects/conda/en/latest/user-guide/install/macos.html#install-macos-silent). Afterwards you have to register the bioconda and conda-forge channels as a package source for conda.

$ conda config --add channels conda-forge
$ conda config --add channels bioconda
$ conda config --add channels r

Install R, and the JACS package which is required for infercnv.

$ conda install -c conda-forge r-base=4.1
$ conda install -c conda-forge r-rjags

Installation using R

> install.packages("BiocManager", repos = "https://cloud.r-project.org")
> BiocManager::install(c("Seurat", "ggplot2", "dplyr", "presto", "infercnv", "SingleR", "celldex", "scmap", "navinlabcode/copykat", "chris-mcginnis-ucsf/DoubletFinder", "bm2-lab/scLearn"))
> BiocManager::install("WubingZhang/scAnalyzer")

Documentation

> ?scAnalyzer
> ?CellTypeAnnotator
> ?cnvInfer

WubingZhang/scAnalyzer documentation built on Jan. 30, 2023, 10:11 p.m.