Training materials
Difficulty level: Intermediate
and Scientific topics: Omics or Transcriptomics or Data identity and mapping
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Bioinformatics, Computational Biology, Computer Science, Programming, Coding, Education, Data Science, Transcriptomics, Machine Learning
R for Data Science
•• intermediateBioinformatics Computational biology Machine learning Transcriptomics Computational Biology Coding Programming Data Science Data Analysis Computer Science Machine Learning -
Presentation
FAIRtracks and Omnipy – FAIRtracks interoperability story
•• intermediateData submission, annotation, and curation Data identity and mapping Data quality management Data governance Workflows Data handling -
hands-on tutorial
Bulk RNASeq analysis
•• intermediateTranscriptomics Gene expression Differential gene expression profiling Expression analysis Data analysis NGS RNASeq transcriptomics -
hands-on tutorial
Hands-on for 'Visualization of RNA-Seq results with Volcano Plot in R' tutorial
•• intermediateTranscriptomics transcriptomics interactive-tools -
slides
Slides for 'An introduction to scRNA-seq data analysis' tutorial
•• intermediateTranscriptomics single-cell español -
Tutorial
Tutorial on CARNIVAL
•• intermediateMolecular interactions, pathways and networks Gene expression Omics RNA-Seq Network analysis RNA-Seq analysis HPC Signaling RNAseq, transcriptomics -
Bioinformatics Summer School 2019
•• intermediateProteomics RNA-Seq Omics Statistics and probability Data handling