ScFOCAL
scFOCAL operates through the integration of drug-response transcriptional consensus signatures (TCSs) derived from the LINCS L1000 dataset with multi-subject single-cell RNA sequencing data, and facilitates analysis of drug and cell connectivity as a function of expression discordance from multiple perspectives.
Install / Use
/learn @AyadLab/ScFOCALREADME
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<!-- PROJECT LOGO --> <br /> <div align="center"> <a href="https://github.com/AyadLab/scFOCAL"> <img src="inst/shiny/www/scFOCAL.png" alt="Logo" width="800" height="200"> </a> </div> <br /> <div align="center"> <p align="center"> <strong>(s)ingle-(c)ell (F)ramework for (O)mics-(C)onnectivity and (A)nalysis via (L)1000</strong> <br /> <br /> <a href="https://github.com/AyadLab/scFOCAL"><strong>Explore the docs »</strong></a> <br /> <br /> <a href="https://github.com/AyadLab/scFOCAL/issues">Report Bug</a> · <a href="https://github.com/AyadLab/scFOCAL/issues">Request Feature</a> </p> </div> <!-- TABLE OF CONTENTS --> <details> <summary>Table of Contents</summary> <ol> <li> <a href="#License-agreement">License agreement</a> </li> <li> <a href="#about-scFOCAL">About scFOCAL</a> <!-- <ul> <li><a href="#built-with">Built With</a></li> </ul> --> </li> <li> <a href="#the-scFOCAL-R-Package">The scFOCAL R Package</a> <ul> <li><a href="#prerequisites">Prerequisites</a></li> <li><a href="#installation">Installation</a></li> </ul> </li> <li><a href="#usage">Usage</a></li> <!-- <li><a href="#roadmap">Roadmap</a></li> --> <li><a href="#contributing">Contributing</a></li> <li><a href="#license">License</a></li> <li><a href="#contact">Contact</a></li> <!-- <li><a href="#acknowledgments">Acknowledgments</a></li> --> </ol> </details>License agreement
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The Board of Trustees of the Georgetown University provides scFOCAL (Formerly ISOSCELES) software and code (“Service”) free of charge for non-commercial use only. Use of the Service by any commercial entity for any purpose, including research, is prohibited.
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By using the Service, you agree to be bound by the terms of this Agreement. Please read it carefully.
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You agree not to use the Service for commercial advantage, or in the course of for-profit activities.You agree not to use the Service on behalf of any organization that is not a non-profit organization. Commercial entities wishing to use this Service should contact Georgetown University Office of Technology Commercialization.
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THE SERVICE IS OFFERED “AS IS”, AND, TO THE EXTENT PERMITTED BY LAW, Georgetown MAKES NO REPRESENTATIONS AND EXTENDS NO WARRANTIES OF ANY KIND,EITHER EXPRESS OR IMPLIED. GEORGETOWN SHALL NOT BE LIABLE FOR ANY CLAIMS OR DAMAGES WITH RESPECT TO ANY LOSS OR OTHER CLAIM BY YOU OR ANY THIRD PARTY ON ACCOUNT OF, OR ARISING FROM THE USE OF THE SERVICE. YOU HEREBY AGREE TO DEFEND AND INDEMNIFY GEORGETOWN, ITS TRUSTEES, EMPLOYEES, OFFICERS, STUDENTS, AGENTS, FACULTY, REPRESENTATIVES, AND VOLUNTEERS (“GEORGETOWN INDEMNITEES”) FROM ANY LOSS OR CLAIM ASSERTED AGAINST GEORGETOWN INDEMNITEES ARISING FROM YOUR USE OF THE SERVICE.
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All rights not expressly granted to you in this Agreement are reserved and retained by Georgetown or its licensors or content providers. This Agreement provides no license under any patent.
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You agree that this Agreement and any dispute arising under it is governed by the laws of the State of Washington DC, United States of America, applicable to agreements negotiated, executed, and performed within DC.
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Subject to your compliance with the terms and conditions set forth in this Agreement, Georgetown grants you a revocable, non-exclusive, non-transferable right to access and make use of the Service.
About scFOCAL
scFOCAL (formerly ISOSCELES) operates through the integration of drug-response transcriptional consensus signatures (TCSs) derived from the LINCS L1000 dataset with multi-subject single-cell RNA sequencing data, and facilitates analysis of drug and cell connectivity as a function of expression discordance from multiple perspectives.
<p align="left"> <a href="https://www.nature.com/articles/s41467-025-67783-5"><strong>You can find the scFOCAL paper at Nature Communications here! »</strong></a> </p>Please cite the following when using scFOCAL:
Suter, R.K., Jermakowicz, A.M., Veeramachaneni, R. et al. Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations. Nat Commun 17, 99 (2026). https://doi.org/10.1038/s41467-025-67783-5
scFOCAL is available via shinyapps.io, or as a standalone R package.
<p align="left"> <a href="https://robert-k-suter.shinyapps.io/isosceles/"><strong>You can find scFOCAL on shinyapps.io here! »</strong></a> </p>Due to the inherent large size of scRNAseq datasets, we highly recommend installing the scFOCAL R package to run the application locally.
<p align="right">(<a href="#readme-top">back to top</a>)</p>The scFOCAL R Package
Prerequisites
The scFOCAL R package for R > 4.3.0 can be installed with devtools.
Installation of devtools in R:
# Install devtools from CRAN
install.packages("devtools")
# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("r-lib/devtools")
scFOCAL requires the following additional R packages:
library(shiny)
library(Seurat)
library(ggplot2)
library(tibble)
library(cowplot)
library(viridis)
library(dplyr)
library(ggsci)
library(ggrepel)
library(tidyverse)
library(plotly)
library(htmlwidgets)
library(reshape2)
library(Hmisc)
library(corrplot)
library(pheatmap)
library(grid)
library(MAST)
library(shinydashboard)
library(shinythemes)
library(scales)
library(ggforce)
library(ggpubr)
library(EnhancedVolcano)
library(DT)
library(lme4)
library(edgeR)
library(ComplexHeatmap)
Some of these dependencies will need to be installed via Bioconductor.
Installation of BiocManager:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(version = "3.17")
and to install core bioconductor packages:
BiocManager::install()
Installation
Using devtools, the scFOCAL R package can be installed from the source file. With all dependencies satisfied, installation should take less than 5 minutes.
devtools::install_github("AyadLab/scFOCAL")
Usage
Follow this brief tutorial below to familiarize yourself with the application.
Launch the scFOCAL application
Once the R package is installed, launching the scFOCAL GUI is as easy as the following:
library(scFOCAL) # load the scFOCAL library including necessary drug signature data
scFOCAL::runscFOCAL() # launch the scFOCAL shiny GUI
Step 1. - Data Upload
scFOCAL takes scRNAseq input in the form of a Seurat object saved as an RDS file.
<div align="center"> <a href="https://github.com/AyadLab/scFOCAL"> <img src="images/01_dataUpload.png" alt="data upload" width="600" height="153"> </a> </div>Simply choose your file to upload and allow the app to load the Seurat object into the processing environment. Once it is fully loaded, you will see a prompt for the successful upload and to proceed to the pre-processing step.
You can download a small example RDS file of a seurat object subsetted from our data presented within our manuscript here:
<p align="left"> <a href="https://drive.google.com/u/0/uc?id=1Q-OqX27l9SRFX4iaJ1eFlXacUHk1vSPe&export=download"><strong>Download a subsampled version of our processed Seurat object available on GEO! »</strong></a> </p>Please note - this sub-sampled object only contains 500 out of greater than 100,000 cells analyzed within our manuscript to facilitate an accessible usage example. Findings from this subsample will not be representative of those resulting from analysis of the full scRNAseq analyzed within the manuscript. Subsampling was performed as follows:
library(Seurat)
set.seed(1)
obj_toSub <- readRDS(file = "seuratObj.RDS")
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