zhangxf-ccnu / scmoo

scMOO

R package supporting the paper "Imputing dropouts for single-cell RNA sequencing based on multi-objective optimization".

Contents of this archive

This archive contains:

(1) pkg: subdirectory that contains the R package.

(2) scMOO_1.1.pdf: reference manual.

The scMOO package has the following R-package dependencies: keras, tensorflow and rsvd. The dependent packages will be automatically installed along with scMOO. You can use the following commands to install scMOO from GitHub.

Installation

Step 1. If the devtools package has not been installed, install the devtools package first. Invoke R and then type

install.packages("devtools")

Step 2. Load the devtools package.

library("devtools")

Step 3. Install the scMOO package from GitHub.

install_github("Zhangxf-ccnu/scMOO", subdir="pkg")

Quick start

Step 1. Load the library scMOO in R console, by running

library(scMOO)

Step 2. Taking the PBMC_CL dataset as an example, run the following code:

data("PBMC_CL")

result <- scMOO(PBMC_CL, percent=0)

For detailed usages, please refer to "scMOO_1.1.pdf".

Tutorial

A tutorial with examples of cell clustering (downstream experiment) illustrating the usage of scMOO is available at: scMOO-tutorial.html

Contact

Please do not hesitate to contact Miss Ke Jin [email protected] or Dr. Xiao-Fei Zhang [email protected] to seek any clarifications regarding any contents or operation of the archive.