DOI: 10.5281/zenodo.10011621
title: Repository for Single Cell RNA Sequencing Analysis of The EMT6 Dataset

description: Table of Contents

Main Description
File Descriptions
Linked Files
Installation and Instructions
 
 
 
1. Main Description
---------------------------
This is the Zenodo repository for the manuscript titled "A TCR β chain-directed antibody-fusion molecule that activates and expands subsets of T cells and promotes antitumor activity.". The code included in the file titled `marengo_code_for_paper_jan_2023.R` was used to generate the figures from the single-cell RNA sequencing data.
The following libraries are required for script execution:

Seurat
scReportoire
ggplot2
stringr
dplyr
ggridges
ggrepel
ComplexHeatmap
 
 
File Descriptions
---------------------------

The code can be downloaded and opened in RStudios.
The "marengo_code_for_paper_jan_2023.R" contains all the code needed to reproduce the figues in the paper
The "Marengo_newID_March242023.rds" file is available at the following address: https://zenodo.org/badge/DOI/10.5281/zenodo.7566113.svg  (Zenodo DOI: 10.5281/zenodo.7566113).
The "all_res_deg_for_heat_updated_march2023.txt" file contains the unfiltered results from DGE anlaysis, also used to create the heatmap with DGE and volcano plots.
The "genes_for_heatmap_fig5F.xlsx" contains the genes included in the heatmap in figure 5F.
 
 
Linked Files
---------------------
 
This repository contains code for the analysis of single cell RNA-seq dataset. The dataset contains raw FASTQ files, as well as, the aligned files that were deposited in GEO. The "Rdata" or "Rds" file was deposited in Zenodo. Provided below are descriptions of the linked datasets:
 
Gene Expression Omnibus (GEO) ID: GSE223311(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE223311)

Title: Gene expression profile at single cell level of CD4+ and CD8+ tumor infiltrating lymphocytes (TIL) originating from the EMT6 tumor model from mSTAR1302 treatment.
Description: This submission contains the "matrix.mtx", "barcodes.tsv", and "genes.tsv" files for each replicate and condition, corresponding to the aligned files for single cell sequencing data.
 Submission type: Private. In order to gain access to the repository, you must use a reviewer token (https://www.ncbi.nlm.nih.gov/geo/info/reviewer.html).
 
Sequence read archive (SRA) repository ID: SRX19088718 and SRX19088719

Title: Gene expression profile at single cell level of CD4+ and CD8+ tumor infiltrating lymphocytes (TIL) originating from the EMT6 tumor model from mSTAR1302 treatment.
Description:  This submission contains the **raw sequencing** or `.fastq.gz` files, which are tab delimited text files.
Submission type: Private. In order to gain access to the repository, you must use a reviewer token (https://www.ncbi.nlm.nih.gov/geo/info/reviewer.html).
 
Zenodo DOI: 10.5281/zenodo.7566113(https://zenodo.org/record/7566113#.ZCcmvC2cbrJ)

 Title: A TCR β chain-directed antibody-fusion molecule that activates and expands subsets of T cells and promotes antitumor activity.
Description:  This submission contains the "Rdata" or ".Rds" file, which is an R object file. This is a necessary file to use the code.
Submission type: Restricted Acess. In order to gain access to the repository, you must contact the author.
 
 
 
Installation and Instructions
--------------------------------------
The code included in this submission requires several essential packages, as listed above. Please follow these instructions for installation:
 
> Ensure you have R version 4.1.2 or higher for compatibility.
 
> Although it is not essential, you can use R-Studios (Version 2022.12.0+353 (2022.12.0+353)) for accessing and executing the code.
 
1. Download the *"Rdata" or ".Rds"  file from Zenodo (https://zenodo.org/record/7566113#.ZCcmvC2cbrJ) (Zenodo DOI: 10.5281/zenodo.7566113).
2. Open R-Studios (https://www.rstudio.com/tags/rstudio-ide/) or a similar integrated development environment (IDE) for R.
3. Set your working directory to where the following files are located:

marengo_code_for_paper_jan_2023.R
Install_Packages.R
Marengo_newID_March242023.rds
genes_for_heatmap_fig5F.xlsx
all_res_deg_for_heat_updated_march2023.txt
 
You can use the following code to set the working directory in R:
> setwd(directory)
 
4. Open the file titled "Install_Packages.R" and execute it in R IDE. This script will attempt to install all the necessary pacakges, and its dependencies in order to set up an environment where the code in "marengo_code_for_paper_jan_2023.R" can be executed.
5. Once the "Install_Packages.R" script has been successfully executed, re-start R-Studios or your IDE of choice.
6. Open the file "marengo_code_for_paper_jan_2023.R" file in R-studios or your IDE of choice.
7. Execute commands in the file titled "marengo_code_for_paper_jan_2023.R" in R-Studios or your IDE of choice to generate the plots.