Web-based Shiny App for browsing and on-demand analysis of Strongyloides spp RNA-seq datasets.
This app is deployed via Shinyapps.io
For more information, please see the G3 paper associated with this project. See also the GitHub repo for this app's preprocessing pipeline.
This repository contains source code for the web-based Strongyloides RNA-seq Browser. This app is deployed via Shinyapps.io but can also be run locally. See App Setup and App Features sections below for additional details.
Data preprocessing pipelines and example analyses can be found at the Bryant, DeMarco, and Hallem (2021) repository.
The sections below describe the contents of the primary subfolders within this repository:
This folder contains pre-processed data files, including study design files, gene annotations, and digital gene expression lists (vDGEList) containing variance-stabilized, filtered, TMM-normalized RNA-seq data.
Server files for the Shiny app.
User interface files for the Shiny app. Includes custom css and additional README files with methods details.
Static files that can be interactively downloaded within the Strongyloides RNA-seq Browser environment.
To access a stable deployment of the Strongyloides RNA-seq Browser Web App, please visit: hallemlab.shinyapps.io/strongyloides_rnaseq_browser/
To run the latest version locally from GitHub, use the following command in R/RStudio:
library(shiny)
shiny::runGitHub(repo = 'Strongyloides_RNAseq_Browser', username = 'HallemLab')
To run a specific release locally use the following commands in R/RStudio:
-
For PCs --
library(shiny)
shiny::runUrl('https://github.com/HallemLab/Strongyloides_RNAseq_Browser/archive/<RELEASE_VERSION>.zip') -
For Macs --
library(shiny)
shiny::runUrl('https://github.com/HallemLab/Strongyloides_RNAseq_Browser/archive/<RELEASE_VERSION>.tar.gz')
Please note: the download step for runURL/runGitHub takes a substantial amount of time. We recommend downloading this archive and running the application locally.
The Strongyloides RNA-seq Shiny Browser enables users to browse publicly available Strongyloides bulk RNA-seq datasets and perform on-demand analyses including differential expression and gene set enrichment. Data from the following species are currently included: S. stercoralis, S. ratti, S. papillosus, and S. venezuelensis. The app permits browsing RNA-seq data in two modes:
- Browse by Life Stage Mode
- Browse by Gene Mode
Features of the app include:
- Search for gene(s) of interest using stable geneIDs or keywords
- Extract gene expression values for genes of interest
- Display gene expresion across life stages as a heatmap (all genes of interest) or a boxplot (individual genes)
- Display gene expression across life stages for individual genes and their known Strongyloides homologs
- Download log2 counts per million expression for genes of interest as .xslx
- On demand limma-voom-based pairwise differential gene expression analysis
- Display results as interactive volcano plots and datatables
- Download results as .pdf (plots) or .xlsx (datatables)
- Gene set enrichment analysis using the clusterProfiler R package and an Ensembl Compara protein family set established by Hunt et al 2016. (Browse By Life Stage Mode)
- Display results as bubble plot and interactive datatable
- Download results as .pdf (plots) or .xlsx (datatables)
- Download raw/pre-processed data using user-friendly dropdown menu
- Study design files (.csv)
- Log2 counts per million expression for all genes and all samples (.csv)
- Variance-stabilized DGEList object (R object; primary data input for the app)
- Raw expression data for genes discarded during low-count filterering (.csv)
- Shiny - UI framework
- kallisto - Lightweight RNA-seq pseudoalignment method
- limma - Diferential gene expression
- clusterProfiler - Gene set enrichment analysis
- Strongyloides RNA-seq datasets:
- WormBase ParaSite - Gene annotations and reference transcriptomes
- DIYTranscriptomics - Virtual asynchronous course where the authors learned best practices for RNA-seq data analysis; provided primary pipeline for data pre-processing and analysis
This project is licensed under the MIT License.
Updated by A.S.B. on approximately 11-3-21 to include S. stercoralis free-living male RNA-seq data published by Gonzalez Akimori et al 2021.