README file for R package supporting the paper "scTSSR: gene expression recovery for single-cell RNA sequencing using two-side sparse self-representation".

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

Installation

Step 1. If the devtools package has been not installed, install the devtools package first.

install.packages("devtools")

Step 2. Load the devtools package.

library("devtools")

Step 3. Install the scTSSR package from GitHub.

install_github("Zhangxf-ccnu/scTSSR")

Useage

Load the library scTSSR in R console, by running

library(scTSSR)

Taking the baron the dataset as an example, run the following code:

data("baron")

baron_imputation_result <- scTSSR(baron$count.samp, percent=0.05, learning\_rate=0.0001, epochs=100)

For detialed usages, please refer to "scTSSR-manual.pdf".

Codes for reproducing the three downstream analyses (such as differential expression analysis, cell clustering analysis and pseudotime analysis) are available in scTSSR-scTSSR2_experiments_codes and Zenodo website with .

Contact

Please do not hesitate to contact Miss Ke Jin (kej13@mails.ccnu.edu.cn) or Dr. Xiao-Fei Zhang (zhangxf@mail.ccnu.edu.cn) to seek any clarifications regarding any contents or operation of the archive.