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Applying network-level analysis to the RNA-seq data from The Cancer Genome Atlas pan-cancer dataset

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Notebook of RNA-Seq analysis using DIGGER

Applying DIGGER mode: network-level analysis to the RNA-seq data from The Cancer Genome Atlas pan-cancer dataset. Using the structure annotation of isoforms and their expression level, DIGGER constructs a condition-specific PPI.

Data Sources

  • The transcript expressions using RNAseq were obtained from the Cancer Genome Atlas pan-cancer dataset.

  • The BioMart tool was used to annotate and to map genes, transcripts and proteins.

  • BioGRID: The protein interactions database was used to generate the PPI.pkl file.

  • 3did and DOMINE: two domains interactions databases were used to generate the DDI.pkl file.

For more Details check out DIGGER

Web tool: https://exbio.wzw.tum.de/digger/

Github Link: https://github.com/louadi/DIGGER

Dependencies

The notebook requires the following libraries:

NetworkX

pandas

Cite

If you use DIGGER, please cite:

Zakaria Louadi, Kevin Yuan, Alexander Gress, Olga Tsoy, Olga V Kalinina, Jan Baumbach, Tim Kacprowski*, Markus List*: DIGGER: exploring the functional role of alternative splicing in protein interactions, Nucleic Acids Research, https://doi.org/10.1093/nar/gkaa768 (*joint last author)

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Applying network-level analysis to the RNA-seq data from The Cancer Genome Atlas pan-cancer dataset

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