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ACE2_modulating_drugs

Code for reproducing the results of our study titled "Systematic cell line-based identification of drugs modifying ACE2 expression" by Sanju Sinha*, Kuoyuan Cheng*, Alejandro A. Schäffer, Kenneth Aldape, Eyal Schiff, and Eytan Ruppin†.

Additional data needed

The Level 3 LINCS l1000 data should be downloaded from the GEO database (GEO dataset identifiers given below) and put into the "data" folder with the following file names:

  • Phase 1 data (GSE92742): data/GSE92742_Broad_LINCS_Level3_INF_mlr12k_n1319138x12328.gctx
  • Phase 2 data (GSE70138): data/GSE70138_Broad_LINCS_Level3_INF_mlr12k_n345976x12328_2017-03-06.gctx

Software dependencies

R was used for all analysis. Additional R packages required for analysis include:

  • data.table
  • cmapR
  • limma
  • affy
  • GEOquery
  • stringr
  • fgsea

Additional R packages required for plotting the figures include:

  • ggplot2
  • ggrepel
  • readxl
  • ggpubr
  • gridExtra
  • grid
  • lattice

Summary of folders and files

The "data" folder contains processed data used for various analysis; The "analysis" folder contains various R scripts for the analyses in the study; The "plot" folder contains R scripts for generating the figures in the manuscript.

Specifically, key scripts in the "analysis" folder include:

  • run.cmap.de.R: for running differential expression (DE) analysis on the CMAP data
  • gsea.R: for running drug class enrichment analysis on the DE results
  • geo.de.R: an example of DE analysis on a dataset from GEO

The other scripts in this folder are either files containing functions sourced by other scripts, or scripts used for selecting the relevant samples/datasets or preparing the samples for analysis.

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Identification of ACE2 expression-modulating drugs

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