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

Rstudio session with common bulk and single cell RNAseq packages such as DESeq2, Seurat and clusterProfiler.

Webpage

R, Rstudio

Cirrocumulus

Cirrocumulus is an interactive visualization tool for large-scale single-cell genomics data.

Webpage

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

Remotes

BiocManager

GenomeInfoDb

seurat-wrappers

tidyverse

clusterProfiler

seurat-data

RColorBrewer

DOSE

annotables

pheatmap

org.Hs.eg.db

seurat-disk

ggrepel

org.Mm.eg.db

cowplot

org.Dm.eg.db

Seurat

pathview

patchwork

DEGreport

sctransform

tximport

DESeq2

AnnotationHub

Signac

ensembldb

apeglm

ggnewscale

rhdf5

slingshot

gprofiler2

Courses

The available courses are:

Course Title

Course Code

Description

Links

Programming Language

Introduction to
bulk RNAseq
analysis

Intro_to_bulkRNAseq

A 3-day course to introduce bulk RNAseq analysis, from data alignment to bioinformatics analysis

Webpage

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.