4 materials found

Related resources: Transcriptomics dataset 


Transcriptomics - CLIP-Seq data analysis from pre-processing to motif detection

Training material for all kinds of transcriptomics analysis. Questions of the tutorial: - How is raw CLIP-Seq data processed and analysed? - How do I find binding motifs and targets for a protein (e.g., RBFOX2)? Objectives of the tutorial: - Remove Adapters, Barcodes and Unique Molecular...

Resource type: Tutorial

Transcriptomics - CLIP-Seq data analysis from pre-processing to motif detection https://tess.elixir-europe.org/materials/transcriptomics-clip-seq-data-analysis-from-pre-processing-to-motif-detection Training material for all kinds of transcriptomics analysis. Questions of the tutorial: - How is raw CLIP-Seq data processed and analysed? - How do I find binding motifs and targets for a protein (e.g., RBFOX2)? Objectives of the tutorial: - Remove Adapters, Barcodes and Unique Molecular Identifiers (UMIs) from the reads - Align trimmed reads with STAR - De-duplicate the read library - Inspect the read mapping and de-duplication quality - Perform peak calling with PEAKachu - Analyse the peaks and find potential binding motifs and targets - Check the quality of the peak calling
Transcriptomics - Visualization of RNA-Seq results with CummeRbund

Training material for all kinds of transcriptomics analysis. Questions of the tutorial: - How are RNA-Seq results stored? - Why are visualization techniques needed? - How to select our desired subjects for differential gene expression analysis? Objectives of the tutorial: - Manage RNA-Seq...

Resource type: Tutorial

Transcriptomics - Visualization of RNA-Seq results with CummeRbund https://tess.elixir-europe.org/materials/transcriptomics-visualization-of-rna-seq-results-with-cummerbund Training material for all kinds of transcriptomics analysis. Questions of the tutorial: - How are RNA-Seq results stored? - Why are visualization techniques needed? - How to select our desired subjects for differential gene expression analysis? Objectives of the tutorial: - Manage RNA-Seq results - Extract the desired subject for differential gene expression analysis - Visualize information
Transcriptomics - Differential abundance testing of small RNAs

Training material for all kinds of transcriptomics analysis. Questions of the tutorial: - What small RNAs are expressed? - What RNA features have significantly different numbers of small RNAs targeting them between two conditions? Objectives of the tutorial: - Process small RNA-seq datasets...

Resource type: Tutorial

Transcriptomics - Differential abundance testing of small RNAs https://tess.elixir-europe.org/materials/transcriptomics-differential-abundance-testing-of-small-rnas Training material for all kinds of transcriptomics analysis. Questions of the tutorial: - What small RNAs are expressed? - What RNA features have significantly different numbers of small RNAs targeting them between two conditions? Objectives of the tutorial: - Process small RNA-seq datasets to determine quality and reproducibility. - Filter out contaminants (e.g. rRNA reads) in small RNA-seq datasets. - Differentiate between subclasses of small RNAs based on their characteristics. - Identify differently abundant small RNAs and their targets.
Transcriptomics - De novo transcriptome reconstruction with RNA-Seq

Training material for all kinds of transcriptomics analysis. Questions of the tutorial: - What genes are differentially expressed between G1E cells and megakaryocytes? - How can we generate a transcriptome de novo from RNA sequencing data? Objectives of the tutorial: - Analysis of RNA...

Resource type: Tutorial

Transcriptomics - De novo transcriptome reconstruction with RNA-Seq https://tess.elixir-europe.org/materials/transcriptomics-de-novo-transcriptome-reconstruction-with-rna-seq Training material for all kinds of transcriptomics analysis. Questions of the tutorial: - What genes are differentially expressed between G1E cells and megakaryocytes? - How can we generate a transcriptome de novo from RNA sequencing data? Objectives of the tutorial: - Analysis of RNA sequencing data using a reference genome - Reconstruction of transcripts without reference transcriptome (de novo) - Analysis of differentially expressed genes