thecobb / martin_et_al_cell_2019

Scripts and data files used to generate the figures of the Crohn's single-cell RNA-seq paper "Single-cell analysis of Crohn’s disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy"

Making the figures

Requirements

Tested on macOS

1. R
2. R packages:
   • viridis
   • RColorBrewer
   • gplots
   • Matrix
   • Matrix.utils
   • seriation
   • scDissector
3. Downloaded and unzipped version of this repository on a local path.

Running the scripts in R

1. Assuming martin_et_al_cell_2019 is the local path of the repository we need to load the script files:

source("martin_et_al_cell_2019/scripts/figures_main.R")

2. And then make figures 1-5 and supplumentary figures:

make_martin_et_al_figures("martin_et_al_cell_2019/",download_data = F)

Output

Figure will be generated in:

• martin_et_al_cell_2019/output/main_figures/
• martin_et_al_cell_2019/output/supp_figures/

Tables will be generated in:

• martin_et_al_cell_2019/output/tables/

Clustering

Requirements

Tested on linux LSF HPC. Due to lack of support of some of the depdendencies, the script cannot run on macOS.

1. R
2. R packages:
   • Matrix
   • Matrix.utils
   • gplots
   • seriation
   • tglkmeans
   • scDissector
3. Downloaded and unzipped version of this repository on a local path.

Running the scripts in R

Assuming martin_et_al_cell_2019 is the local path of the repository, the following script will run the clustering distributedly on LSF:

source("martin_et_al_cell_2019/scripts/clustering/run_clustering_ileum.r")

Alternatively, clustering can be run locally:

source("martin_et_al_cell_2019/scripts/clustering/run_clustering_ileum_local.r")

Note: Each run of the clustering might produce slightly different results due to different random seeds.