Pagoda2 is an R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets. The methods were optimized to rapidly process modern scRNAseq datasets, which are both large (approximately 1e6 cells or greater) and sparse. The package provides methods for quality control, filtering, clustering, visualization, differential expression, cross-cutting aspects/states, and geneset/pathway overdispersion analysis. The companion frontend application allows users to figure out which gene expression patterns give rise to different subpopulations within the data. The application allows users to inspect the gene expression patterns of subpopulations through annotated gene sets and pathways, including Gene Ontology (GO) categories. Users may also highlight certain clusters and perform differential expression from their browsers via the frontend application.
Note that pagoda2 is an R package developed for analyzing standalone scRNAseq datasets. For joint analysis of multiple datasets, please see the package conos. (The package pagoda2 is primarily used to preprocess input datasets for conos.)
Several methods within this package were developed based on the originals implemented within SCDE and PAGODA1.
Basic Walkthrough * HTML version * Markdown version
To install the stable version from CRAN, use:
To install the latest version of pagoda2, use:
Installation for Debian-based distributions (e.g. Ubuntu):
Installation for Red-Hat-based distributions (e.g. CentOS or Fedora)
We recommend the Homebrew package manager to install require dependencies on Mac OS. Please run the following commands in the terminal:
As of version 0.1.3, pagoda2 should sucessfully install on Mac OS. Furthermore, we encourage Mac OS users to install the package via the binaries on CRAN. However, if there are issues, please refer to the following wiki page for further instructions on installing pagoda2 with Mac OS: Installing pagoda2 for Mac OS
If you are having trouble setting up pagoda2 on your system, an alternative approach to work with pagoda2 is via a Docker container. To use the Docker container, first install docker on your platform and then run the pagoda2 image with the following command in the shell:
docker run -p 8787:8787 -e PASSWORD=pass pkharchenkolab/pagoda2:latestThe first time you run this command, it will pull/download several images—please make sure that you have reliable internet access. You can then point your browser to http://localhost:8787/ to access an Rstudio environment with pagoda2 installed (please log in using credentials username=rstudio, password=pass). Explore the Docker –mount option to allow the Docker image to access your local files.
If you find pagoda2 useful for your publication, please cite:
Nikolas Barkas, Viktor Petukhov, Peter Kharchenko, Simon Steiger,
Rasmus Rydbirk, and Evan Biederstedt (2021). pagoda2: Single Cell
Analysis and Differential Expression. R package version 1.0.12.