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This repo contains the code to build "SGHumanBrainApp", a Shiny web application to explore sex and gender difference in the human brain transcriptome

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SGHumanBrainApp

This repository contains the code for the web app SGHumanBrainApp and the files used to build the app. The link for the SGHumanBrainApp web app is https://joshiapps.cbu.uib.no/GenderRank_app.

Table of Contents

The repo contains the following content:


app.R

Main R script to build the web application using Shiny and shinydashboard. It organizes the information in multiple tabs, and gives the user the possibility to change the adjusted p-value and fold change (FC) threhsold, to see how the different plots vary accordingly.

Data folder

Single-cell RNA-seq

In this folder, all the files needed to build the plots are present. The Unfiltered_DEGs contains all the DEGs as calculated from Seurat, organized by dataset and cell type (original annotation). The Filtered_DEGs instead has the same DEGs, but filtered by several combinations of adjusted p-value and fold change thresholds, again organized by datasets and cell types.

The extra_files contains the files needed to generate the output plots.

Bulk RNA-seq

Some of the results from the bulk RNA-seq analysis are already calculated, while other plots are generated according to the user's input. The two tabs in the app have two corresponding data folder, namely Healthy and pre_result_allreg. Healthy contains the DEGs lists for each study used in each brain region, and they can be downloaded. pre_result_allreg instead contains the plots and data from the comparison across brain regions.

Custom_scripts

The scripts are used to generate all the different files and plots, and to build the Rshiny app.

Brief description of the custom scripts:

www

Single-cell RNA-seq

The www folder contains all plots and images, mainly as PNG, which are displayed for the user to explore the data. The images in Plots were either generated using Generate_output_files.R, while the number of samples etc were generated in the main analysis, which can be found here.

Bulk RNA-seq

Images with information about the datasets per region can be found here.

Notes

  • The bulk RNA-seq app was also developed indipendently, please check the original source here.
  • Because this repo contains a large amount of files (stored with LFS), it is advisable to clone the repo, and NOT download it as a zip folder, using the following command:
git clone https://github.com/aurazelco/SGHumanBrainApp.git

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This repo contains the code to build "SGHumanBrainApp", a Shiny web application to explore sex and gender difference in the human brain transcriptome

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