Transcriptomics Sandbox¶
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In this app you will find material for the Transcriptomics sandbox of the Health Data Science sandbox. This contains courses you can learn from, datasets and tools you can work with for your own research/learning purposes. Items of this sandbox are currently based on Rstudio Server. Rstudio is a web-based integrated development environment for R programming language, including R Markdown, code, and data. Typically, each item includes a dedicated webpage with additional information, guides, and material.
Available Items¶
Items are periodically added to this app and can be chosen from the menu. Each item can be a course, a setup to work with specific software, a research example and comes with all necessary packages installed, eventual notebooks with computer code and explanations, and a dedicated webpage with additional material (notes, slides, recordings, ...).
The available tools are:
Tool Name |
Description |
Links |
Programming Language |
|---|---|---|---|
RNAseq in |
Rstudio session with common bulk and single cell RNAseq packages such as DESeq2, Seurat and clusterProfiler. |
R, Rstudio |
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Cirrocumulus |
Cirrocumulus is an interactive visualization tool for large-scale single-cell genomics data. |
Python, JavaScript |
Packages for RNAseq in Rstudio¶
A few R packages have been installed in order to work with RNAseq data. Other packages and dependencies might be installed but are not shown here.
CRAN |
Bioconductor |
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Courses¶
The available courses are:
Course Title |
Course Code |
Description |
Links |
Programming Language |
|---|---|---|---|---|
Introduction to |
Intro_to_bulkRNAseq |
A 3-day course to introduce bulk RNAseq analysis, from data alignment to bioinformatics analysis |
R, Bash, Nextflow |
Loading course materials¶
Materials for courses are available under /usr/<course_code>. To work with the course materials, use a symlink to link the course to the /work. For example, in the Rstudio session, to select the Intro to bulk RNAseq course material, enter the following line in the terminal tab of Rstudio:
$ ln -s /usr/Intro_to_bulkRNAseq /work/Intro_to_bulkRNAseq
Save your work¶
Everything saved in the /work folder will be saved in your personal folder after you finish your job in UCloud.
Note
Symlinks created in /work will not save the corresponding folder after the job is completed. If you want a copy of the material, the actual folder should be copied from the original path to /work via the terminal interface, e.g.:
$ cp -r /usr/Intro_to_bulkRNAseq /work/Intro_to_bulkRNAseq
Additional options¶
Before submitting the app, you can choose the amount of resources you need. Additionally, you can add folders so that they will be visible when using the app. Adding folders is useful if:
You want to use a folder containing your own data and code, with which you want to perform analysis with the Transcriptomics tools of a course/module.
You want to continue working on the material from a previous session of the Transcriptomics Sandbox. In such a case, add the folder containing the material using the Add folder optional parameter.
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