SCEPTRE is a method for single-cell CRISPR screen analysis. This repository contains code to reproduce all analyses reported in the following paper, which introduces the SCEPTRE method:
Conditional resampling improves calibration and sensitivity in single-cell CRISPR screen analysis
T. Barry, X. Wang, J. Morris, K. Roeder, and E. Katsevich (2021)
preprint available at bioRxiv
Note that there are two sceptre R packages: an in-house package intended for manuscript reproduction purposes only, and a separate package intended for new data analysis purposes. If you would like to use SCEPTRE to analyze your own data, please visit the Github repository or website of the latter package.
This repository contains two high-level directories: sceptre_package and sceptre_paper. The sceptre_package directory contains the (in-house) sceptre R package and some shell and R scripts to help run the method at scale. The sceptre_paper directory contains code required to reproduce all analyses reported in Barry et al. 2020. Code in sceptre_paper relies heavily on code in sceptre_package; by contrast, code in sceptre_package does not depend at all on code in sceptre_paper.
- sceptre_package: Contains the (in-house)
sceptrepackage and helper scripts.- sceptre_package/sceptre: (in-house)
sceptrepackage itself. - sceptre_package/sceptre_at_scale: Helper shell and R scripts.
- sceptre_package/sceptre: (in-house)
- sceptre_paper: Code for reproducing Barry et al. 2020.
- sceptre_paper/analysis_drivers: R scripts for reproducing data analysis.
- sceptre_paper/katsevich2020: Additional R package containing functions called by scripts in sceptre_paper directory.
- sceptre_paper/manuscript: .tex manuscript.
- sceptre_paper/nb_regression_at_scale: Code for running large-scale negative binomial regression.
- sceptre_paper/plotting: R scripts to create manuscript figures.
- sceptre_paper/simulations: R scripts for running simulations.
- sceptre_paper/utilities: Shell and R scripts for reproducing the entire analysis.
The code was executed across two machines: a computer cluster running R version 3.6.1 and Linux kernel 4.4.180-102, and a Macbook running R version 4.0.2 and Darwin kernel version 20.1.0. In addition, the following R packages were used:
- bigstatsr 1.2.3
- cowplot 1.1.0
- fst 0.9.4
- furrr 0.2.0
- ggpubr 0.4.0
- ggrepel 0.9.1
- katsevich2020 0.1.0
- MASS 7.3.53
- mgcv 1.8-33
- monocle 2.18.0
- openxlsx 4.2.2
- R.matlab 3.6.2
- rhdf5 2.33.11
- scales 1.1.1
- sceptre 1.0.0
- Seurat 3.2.2
- sn 1.6.2
- tidyverse 1.3.0
- VGAM 1.1.3
The scripts to reproduce the analysis will (try to) download the packages automatically.
Git clone the SCEPTRE repository:
git clone https://github.com/Katsevich-Lab/sceptre-manuscript
Next, navigate to the sceptre_paper/utilities directory, open the run_everything.bash script, and follow the instructions therein. The run_everything.bash script reproduces the entire analysis, from downloading the data to creating the figures. All analysis results (including intermediate files) are available on Box. Parts of the analysis therefore can be reproduced by loading the intermediate results files instead of recomputing them.