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Code for Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients

Public repository containing research code for the TCGA PanCanAtlas Splicing project accompanying the manuscript Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients

The code is organized in several sub-directories, which contain the following content:

  • alt_splice Code concerning the detection and analysis of alternative splicing events.

    • events
      Wrapper code for the detection of splicing events in the cohort using SplAdder.

    • event_stats
      Code for visualising the event type distributions and number of alternative splicing events detected per cancer type.

    • filtering
      Code implementing various filters on the AS events, based on read coverage, min delta PSI, etc.

    • complexity
      Detection of neo-junctions predominantly present in cancer samples but absent from annotation or the GTEx outgroup.

    • splice_outliers
      Code for detection and visualization of splicing outliers.

    • tumor_vs_normal_rank
      Identification and ranking of tumor specific introns.

    • tumor_vs_normal_stats
      Assessment of events detected in tumor samples vs normal samples.

    • tumor_vs_normal_test
      Differential testing of tumor vs normal samples on sets of subsamples per cancer type.

  • neoepitopes
    Contains code for the visualization of results on the prediction of neo-epitopes.

  • peptide_generation
    Code concerned with generating peptides from splice-graphs.

  • sample_processing_rna
    Code for pre-processing and alignment of the RNA-Seq data, including expression counting, the collection of usage statistics, and construction of splicing graphs.

  • sqtl
    Visualization scripts for the sQTL analyses.

  • tSNE_and_heatmap_visualizations
    Code for tSNE embeddings on alternative splicing and expression data as well as scripts for visualization and different highlightings.

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Public repository containing research code for the TCGA PanCanAtlas Splicing project

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  • Python 65.0%
  • Jupyter Notebook 28.7%
  • Shell 4.1%
  • R 2.2%