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Project: protect (GitHub Link)

• protect-master
  • src
    • __init__.py
    • protect
      • version.py
      • qc
        • __init__.py
        • rna.py
      • test
        • test_inputs
          • test_rsem_quant.tsv.tar.gz
          • ci_all_fastq_parameters.yaml
          • ci_mix_bam_fastq_parameters.yaml
          • ci_parameters.yaml
          • test_mhc_haplotype.sum.tar.gz
          • ci_vcf_bedpe_haplotype_expression_parameters.yaml
          • ci_vcf_fastq_parameters.yaml
        • __init__.py
        • ci
          • test_protect.py
          • __init__.py
        • unit
          • test_reporting.py
          • test_snpeff.py
          • test_transgene
          • test_mutation_callers.py
          • test_file_downloads.py
          • test_spawn_antigen_predictors.py
          • __init__.py
          • test_rankboost.py
          • test_alignments.py
      • mutation_translation.py
      • binding_prediction
        • mhcii.py
        • mhci.py
        • common.py
        • __init__.py
      • alignment
        • common.py
        • __init__.py
        • rna.py
        • dna.py
      • mutation_annotation
        • snpeff.py
        • __init__.py
      • addons
        • assess_immunotherapy_resistance.py
        • common.py
        • __init__.py
        • assess_mhc_pathway.py
        • assess_car_t_validity.py
      • common.py
      • __init__.py
      • haplotyping
        • phlat.py
        • __init__.py
      • pipeline
        • defaults.yaml
        • required_entries.yaml
        • ProTECT.py
        • __init__.py
        • input_parameters.yaml
      • mutation_calling
        • muse.py
        • fusion.py
        • somaticsniper.py
        • mutect.py
        • common.py
        • indel.py
        • __init__.py
        • strelka.py
        • radia.py
      • rankboost.py
      • expression_profiling
        • rsem.py
        • __init__.py
  • Flowchart.txt
  • Makefile
  • required_docker_tools.txt
  • attic
    • encrypt_files_in_dir_to_s3.py
    • ProTECT_large.py
    • ProTECT.py
    • precision_immuno.py
    • input_parameters.list
    • __init__.py
    • LICENSE.txt
  • version.py
  • LICENSE
  • setup.py
  • docker
    • Makefile
    • protect.json
    • protect.cwl
    • wrapper.py
    • Makefile.template
    • pipelineWrapper.py
    • Dockerfile
    • Dockerfile.template
  • README.md
  • MANUAL.md
  • .gitignore
  • MANIFEST.in
  • jenkins.sh

ProTECT

Prediction of T-Cell Epitopes for Cancer Therapy

This repo contains the Python libraries for the Precision Immunology Pipeline developed at UCSC.

src/protect/pipeline/ProTECT.py             - The python script for running the pipeline.
src/protect/pipeline/input_parameters.yaml  - The config file for the run that contains all the
                                              necessary parameters for the run.
Flowchart.txt                               - A (super cool) flowchart describing the flow of
                                              the pipeline.

ProTECT uses sequencing information from a patient to predict the neo-epitopes produced in their tumors that can be used in T-cell based, or peptide vaccine based therapies.

All docker images used in this pipeline are available at

                    https://hub.docker.com/u/aarjunrao/

To learn how the pipeline can be run on a sample, head over to the ProTECT Manual

ProTECT is currently in its infancy and is under continuous development. We would appreciate users sharing the level 3 data produced by ProTECT with us such that we can better train our predictive models.