Training materials
Keywords: Data analysis or FAIR or HPC or contributing or jupyter-notebook
and Contributors: Helena Rasche or Janina Müller
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hands-on tutorial
Filter, plot, and explore single cell RNA-seq data with Seurat (R)
• beginner10x R Single Cell jupyter-notebook paper-replication rmarkdown-notebook -
hands-on tutorial
Data visualisation Olympics - Visualization in R
• beginnerSoftware engineering Foundations of Data Science R cyoa jupyter-notebook rmarkdown-notebook -
hands-on tutorial
FAIR data management solutions
•• intermediateFAIR Data management -
hands-on tutorial
RO-Crate in Python
• beginnerFAIR Data, Workflows, and Research jupyter-notebook ro-crate -
hands-on tutorial
Inferring single cell trajectories with Monocle3 (R)
• beginner10x R Single Cell jupyter-notebook paper-replication rmarkdown-notebook -
hands-on tutorial
Python - Coding Style
•• intermediateSoftware engineering Foundations of Data Science jupyter-notebook -
Video, E-learning
FAIR principles in practice for health data
• beginnerComputer science Data management FAIR data Medical informatics Standardisation and normalisation Design Clinical data RDF Knowledge graph Semantic framework FAIR Findability Accessibility Interoperability Reusability -
hands-on tutorial
Inferring single cell trajectories with Scanpy (Python)
• beginnerTranscriptomics 10x Python Single Cell jupyter-notebook paper-replication -
hands-on tutorial
Scripting Galaxy using the API and BioBlend
• beginnerSoftware engineering Development in Galaxy jupyter-notebook -
hands-on tutorial
Python - Subprocess
•• intermediateSoftware engineering Foundations of Data Science jupyter-notebook