From be647f53fd3368eb992cee2d53c783df2961c4f7 Mon Sep 17 00:00:00 2001 From: divyarajsinh6100 <72164951+divyarajsinh6100@users.noreply.github.com> Date: Thu, 1 Oct 2020 16:01:23 +0530 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e29fc40..e15d615 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # scsim -Simulate single-cell RNA-SEQ data using the [Splatter](https://github.com/Oshlack/splatter) statistical framework, which is descrubed [here](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1305-0) but implemented in python. In addition, simulates doublet cells and cells with shared gene-expression programs. This was used to benchmark methods for gene expression program inference in single-cell rna-seq data as described [here](https://www.biorxiv.org/content/early/2018/10/07/310599) +Simulate single-cell RNA-SEQ data using the [Splatter](https://github.com/Oshlack/splatter) statistical framework, which is described [here](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1305-0) but implemented in python. In addition, simulates doublet cells and cells with shared gene-expression programs. This was used to benchmark methods for gene expression program inference in single-cell rna-seq data as described [here](https://www.biorxiv.org/content/early/2018/10/07/310599) run_scsim.py has example code for running a simulation with a given set of parameters. It saves the results in the numpy compressed matrix format which can be loaded into a Pandas dataframe as follows: