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Integrative Analysis Recipe

Stephan Reichl edited this page Aug 7, 2024 · 2 revisions

The Integrative ATAC-seq & RNA-seq Analysis Recipe takes you from unaligned (raw) BAM files derived from matched bulk RNA-seq and bulk ATAC-seq experiments to enrichment analysis results of deviating genes between the modalities (termed epigenetic potential vs relative transcriptional surplus) while providing unsupervised analyses of the integrated dataset and genome browser tracks for quality control.

flowchart LR;
    ngs_fetch_RNA-->rnaseq_pipeline;
    ngs_fetch_ATAC-->atacseq_pipeline;
    rnaseq_pipeline-->genome_tracks_RNA;
    atacseq_pipeline-->genome_tracks_ATAC;
    rnaseq_pipeline-->spilterlize_integrate;
    atacseq_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 and bulk ATAC-seq data (coming soon).
  2. (coming soon) RNA-seq pipeline to quantify gene expression, resulting in count matrices and annotations.
  3. ATAC-seq pipeline to quantify chromatin accessibility at the promoter/TSS locus of each gene, resulting in count matrices and annotations.
  4. Genome Browser Track Visualization for quality control and visual analysis of genomic regions of interest or top hits from downstream analyses.
  5. Split, Filter, Normalize and Integrate Sequencing Data to integrate the two modalities into one common feature space and prepare for downstream analysis.
  6. Unsupervised Analysis for quality control and to understand and visualize similarities and variations between samples of the integrated dataset in the shared feature space.
  7. Differential Analysis with limma to identify and visualize statistically significant gene-promoter-pairs (deviating genes) that differ between modalities despite computational integration.
  8. Enrichment Analysis for biomedical interpretation of differential analysis results using prior knowledge.

Code & Configuration

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Results

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