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ProTECT

Prediction of T-Cell Epitopes for Cancer Therapy

Adapation of ProTECT to use python 3.8 instead of 2.7. Currently have tested a complete run using fastq files from HCC1395 WGS Exome RNA Seq Data, with identical results in both version of python.

Adaptation done using 2to3 and manual bug testing. Manual changes recorded at changes.md. Since s3am is python2, currently is local only, however an untested python3 version of s3am exists here. Continuing to the original README:

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.

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