RNAseq Analysis Recipe

The RNA-seq Analysis Recipe takes you from unaligned (raw) BAM files derived from a bulk RNA-seq experiment to enrichment analysis results of your differentially expressed genes while providing unsupervised analyses and genome browser tracks for quality control.

flowchart LR;
    ngs_fetch-->rnaseq_pipeline;
    rnaseq_pipeline-->genome_tracks;
    rnaseq_pipeline-->spilterlize_integrate;
    spilterlize_integrate-->unsupervised_analysis;
    spilterlize_integrate-->dea_limma;
    dea_limma-->enrichment_analysis;

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Modules

The following Modules are used in this Recipe:

1. (optional) Fetch publicly available bulk RNA-seq data (coming soon).
2. (coming soon) RNA-seq pipeline to quantify gene expression, resulting in count matrices and annotations.
3. Genome Browser Track Visualization for quality control and visual analysis of genomic regions of interest or top hits form downstream analyses.
4. Split, Filter, Normalize and Integrate Sequencing Data for downstream analysis.
5. Unsupervised Analysis for quality control and to understand and visualize similarities and variations between samples.
6. Differential Analysis with limma to identify and visualize statistically significant genes that differ between sample groups using linear models.
7. Enrichment Analysis for biomedical interpretation of differential analysis results using prior knowledge.

Code & Configuration

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Results

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