vkozareva / Analogizer

R package for integrating and analyzing multiple single-cell datasets

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Analogizer

Analogizer is a package for integrating and analyzing multiple single-cell datasets, developed and maintained by the Macosko lab. It relies on integrative non-negative matrix factorization to identify shared and dataset-specific factors.

Installation

Analogizer is written in R and has a few other system requirements (Java) and recommended packages (umap in Python). To install the most recent development version, follow these instructions:

  1. Install R (>= 3.4)
  2. Install Rstudio (recommended)
  3. Make sure you have Java installed in your machine. Check by typing java -version into Terminal or CommandPrompt.
  4. Generate an auth token for the Analogizer repo, making sure to include all repo permissions.
  5. Use the following R commands.
install.packages('devtools')
library(devtools)
install_github('MacoskoLab/Analogizer', auth_token = '<token>')

Troubleshooting (MacOS only -- recommended before step 5)

Installing RcppArmadillo on R>=3.4 requires Clang >= 4 and gfortran-6.1. Follow the instructions below if you have R version 3.4.0-3.4.4. These instructions (using clang4) may also be sufficient for R>=3.5 but for newer versions of R, it's recommended to follow the instructions in this post.

  1. Install gfortran as suggested here
  2. Download clang4 from this page
  3. Uncompress the resulting zip file and type into Terminal (sudo if needed):
mv /path/to/clang4/ /usr/local/ 
  1. Create .R/Makevars file containing following:
# The following statements are required to use the clang4 binary
CC=/usr/local/clang4/bin/clang
CXX=/usr/local/clang4/bin/clang++
CXX11=/usr/local/clang4/bin/clang++
CXX14=/usr/local/clang4/bin/clang++
CXX17=/usr/local/clang4/bin/clang++
CXX1X=/usr/local/clang4/bin/clang++
LDFLAGS=-L/usr/local/clang4/lib

For example, use the following Terminal commands:

cd ~
mkdir .R
cd .R 
nano Makevars

Paste in the required text above and save with Ctrl-X.

Usage

For usage examples and guided walkthroughs, check the vignettes directory of the repo.

About

R package for integrating and analyzing multiple single-cell datasets


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